ArticlePDF Available

Abstract and Figures

Despite the latest research efforts to foster mobility and roaming in heterogeneous Low Power Wide Area Networks (LP-WANs) networks, handover roaming of Internet of Things (IoT) devices is not a success mainly due to fragmentation and difficulties to establish trust across different network domains as well as the lack of interoperability of different LP-WANs wireless protocols. To cope with this issue, this paper proposes a novel handover roaming mechanism for Low Range Wide Area Network (LoRaWAN) protocol that relies on the trusted 5G network to perform IoT device’s authentication and key management, thereby extending the mobility and roaming capabilities of LoRaWAN to global scale. The proposal enables interoperability between 5G network and LoRaWAN, whereby multi Radio Access Technologies IoT (multi-RAT IoT) devices can exploit both technologies interchangeably, thereby fostering novel IoT mobility and roaming use cases for LP-WANs not experimented so far. Two integration approaches for LoRaWAN and 5G have been proposed, either assuming 5G spectrum connectivity with standard 5G authentication or performing 5G authentication over the LoRaWAN network. The solution has been deployed, implemented and validated in a real and integrated 5G-LoRaWAN testbed, showing its feasibility and security viability.
Content may be subject to copyright.
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.
Digital Object Identifier 10.1109/ACCESS.2017.DOI
Enabling Roaming across
Heterogeneous IoT Wireless Networks:
LoRaWAN meets 5G
ELENA M. TORROGLOSA-GARCIA1, JOSE M. ALCARAZ CALERO 1, JORGE BERNAL
BERNABE 2AND ANTONIO SKARMETA 2,
1School of Computing, Engineering and Physical Sciences, University of West of Scotland, United Kingdom (e-mail: elena.torroglosa,
jose.alcaraz-calero@uws.ac.uk)
2University of Murcia, Spain (e-mail: jorgebernal, skarmeta@um.es)
Corresponding author: Elena Torroglosa-Garcia (e-mail: elena.torroglosa@ uws.ac.uk).
This work has been funded by a grant for postdoctoral training and improvement abroad, funded by the Ministry of Employment,
Universities, Enterprise and Environment of the CARM©, through the Seneca Foundation-Agency for Science and Technology of the
Region of Murcia (Spain). This work has been also partially supported by the European Commission H2020 5G-PPP ICT-2016-2 SliceNet
project GA 761913, as well as H2020 European project INSPIRE-5Gplus GA 871808.
ABSTRACT Despite the latest research efforts to foster mobility and roaming in heterogeneous Low Power
Wide Area Networks (LP-WANs) networks, handover roaming of Internet of Things (IoT) devices is not a
success mainly due to fragmentation and difficulties to establish trust across different network domains as
well as the lack of interoperability of different LP-WANs wireless protocols. To cope with this issue, this
paper proposes a novel handover roaming mechanism for Low Range Wide Area Network (LoRaWAN)
protocol that relies on the trusted 5G network to perform IoT device’s authentication and key management,
thereby extending the mobility and roaming capabilities of LoRaWAN to global scale. The proposal
enables interoperability between 5G network and LoRaWAN , whereby multi Radio Access Technologies
IoT (multi-RAT IoT) devices can exploit both technologies interchangeably, thereby fostering novel IoT
mobility and roaming use cases for LP-WANs not experimented so far. Two integration approaches
for LoRaWAN and 5G have been proposed, either assuming 5G spectrum connectivity with standard
5G authentication or performing 5G authentication over the LoRaWAN network. The solution has been
deployed, implemented and validated in a real and integrated 5G-LoRaWAN testbed, showing its feasibility
and security viability.
INDEX TERMS 5G mobile communication, LoRaWAN, Internet of Things, Roaming, Authentication
I. INTRODUCTION
It is foreseen that Internet of Things (IoT) scenarios based on
wireless massive Machine-Type Communications (mMTC)
[1], will scale up to billions of heterogeneous connected
devices in the coming years [2]. The mMTC ecosystem
is composed of a plethora of different kinds of wireless
technologies. On the one hand, Low-Power WAN Area Net-
works (LP-WAN) networks such as LoRa/LoRaWAN [3]
and SigFox [4], each one featuring different functionalities,
data patterns, and capabilities. On the other hand, 3GPP
cellular networks have improved its support on mMTC in
the latest 5G releases [5] compared to previous Long-Term
Evolution (LTE) versions, including Narrowband Internet of
Things (NB-IoT) [6] and LTE-M protocols, although they
still yet lacks of some capabilities supported by other cheaper
non-cellular LP-WAN (Low-Power WAN Area Networks)
networks, such as efficient treatment of sporadic patterns, and
short packet transmissions [7].
In particular, LoRaWAN, that falls in LP-WAN category
[8], is gaining a global momentum and expansion mainly
due to the open-license and economic model as well as the
usage of unlicensed spectrum, which makes it accessible
for everyone [9]. Both, LoRaWAN and 5G IoT wireless
technology are complementary and widely used, but not yet
inter-operable.
This heterogeneity in the IoT wireless landscape is one of
the major challenges to be faced in up-coming years, since
each wireless protocol has its own network mechanisms,
VOLUME 4, 2016 1
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
including authentication protocols, that has led to a high
fragmentation and silos of different kinds of IoT networks.
To cope with these issues, some initial ongoing efforts such
as those being accomplished by the IETF working group IPv6
over LP-WAN, are dealing with inter-operability across het-
erogeneous LP-WAN networks, proposing new adaptations
and network protocols but mainly for OSI layer 3 and layer
4.
Certain use cases like those derived from Intelligent Trans-
port Systems (ITS), including the deployment of vehicles
like trucks, ambulances or drones in different scenarios, can
benefit from the existence of roaming mechanisms. Notice
that in LoRaWAN, roaming is understood as end-device
mobility across different LoRaWAN administrative domains,
regardless of whether it is in the same country or not. These
mobility ITS scenarios imposes specific constrains in terms
of low latency and high bandwidth. In principle, these use
cases are not fully suitable for LP-WAN communications,
which are characterized by low data rates, high latency and
low power features. However, LP-WANs also enables several
IoT use cases based on mMTC communications, and there
are certain IoT mobility use cases that could be perfectly
addressed by LP-WANs, and therefore, supporting handover
roaming in these networks is highly desirable. For instance,
fleet controlling to collect and send operating data of wagon
vehicles could be supported by roaming among LP-WANs
IoT networks.
In this sense, since version LoRaWAN version 1.1 [3],
the LoRaWAN architecture provides support for a simple
handover roaming across different LoRaWAN networks. This
is an initial approach to address the inter-operability between
networks. However, the LoRaWAN roaming requires explicit
agreement negotiations between different administrative do-
mains, in ad-hoc manner, case by case, exchanging sensitive
security information. This makes roaming very difficult in
practice, mainly due to the lack of trust between different
peers. On the other side, roaming is widely supported for
the cellular IoT networks such as LTE-M and NB-IoT using
the control plane of the 4G and 5G networks. However,
these solutions are always trying to provide support for de-
ployments among homogeneous technologies, being mainly
motivated by industrial-centric interests to make a concrete
technologies leading in the IoT sector. This situation leaves
aside more impacting user-centric approaches based on the
enabling of roaming capabilities between heterogeneous IoT
networks deployed using different technologies in order to
allow to best possible use of technology for the final users
making use of multi-interface IoT devices.
To address this challenge, this research work has devised,
implemented and validated a novel handover roaming ca-
pability for LoRaWAN that relies on the 5G architecture to
enlarge the LoRaWAN roaming scope and its authentication
scheme to global scale. Our approach relies on the existing
5G identity management service, AAA and its underlying
federation, as a trusted network service to perform the au-
thentication of IoT devices in roaming LP-WAN networks.
In particular, the solutions leverage the current authentication
and key management processes in LoRaWAN integrating
them with the 5G authentication mechanism.
The novel solution proposed herein enables handover
roaming across different domains in heterogeneous wireless
networks technologies, i.e. LoRaWAN and 5G, thereby open-
ing new possibilities and IoT use cases not experimented
until now. Thus, multi-RAT IoT devices endowed with both,
5G and LoRaWAN user equipment’s can use them inter-
changeably, enabling the usage of the efficient and cheaper
LoRaWAN network equipment in visited domains where
there are not pre-established LoRaWAN agreements, using
SIM-based authentication in the 5G network through the
LoRaWAN protocol.
The proposed roaming architecture brings the following
innovations:
1) It extends the use of the advanced roaming services
provided by 5G cellular networks into LoRaWAN net-
works.
2) It delegates the ad-hoc management of trust relation-
ships in LoRaWAN networks to a third party that will
provide a common and trusted identity management.
3) It leverages the 3GPP services provided under the um-
brella of 5G networks with the new non-3GPP connec-
tivity services associated to LoRaWAN IoT networks.
The rest of this paper is structured as follows. Section III
provides a background on both LoRaWAN and 5G, and
specifically to the security and AAA aspects. Section IV is
devoted to analyse the current related works. Section V is
the core of the paper and provides and analyses two different
approaches for enabling roaming in LoRaWAN with 5G.
Section VI analyses the security of the proposed roaming
approaches. The proof of concept implementation to validate
the solution as well as and the empirical results are described
in section VII. Finally, Section VIII concludes the paper.
II. MOTIVATION
The arrival of the Internet of Things entails new scenarios and
business models related to communication between devices
and to the use and commercialization of necessary com-
munication infrastructures. The integration between cellular
networks and different radio-access technologies, including
unlicensed spectrum (such as LoRaWAN) is a hot topic being
part of the working items defined in the incoming future
3GPP Rel 16 and 17. The incorporation of different types
of devices, both fixed (electrical appliances, smart bulbs,
industrial machinery, urban furniture) and mobile (vehicles,
mobiles, parcels, clothing and accessories, etc.) makes the
use cases more and more varied and complex.
To provide connectivity to these scenarios, it is necessary
to have powerful, robust and extensive networks, and of-
fering flexible connectivity mechanisms to operators is an
interesting solution. Roaming is a mechanism that allows
the mobility of devices between different domains (from
its home domain to another available) allowing to improve
the coverage (sharing antennas to reduce the densification),
2VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
device mobility while transmitting in areas with low coverage
(tracking services) and mobility across multiple networks,
within a given country, internationally or between private and
public ones.
These new opportunities of roaming between networks of
different domains can grew exponentially if we consider the
integration between different technologies, thanks to multi-
RAT IoT devices, to take advantage of the best part of each
one. In particular, the integration of the LoRaWAN networks
that offer long range coverage, low power requirement and
high scalability in the number of devices with the solid
and extended back-end of 5G operators. This model allows
building new strategies. On the one hand, any 5G network
operator will be able to extend business influence to cover
LoRaWAN networks. On other hand, any LoRaWAN net-
work operator will be able to extend the potential users of
their infrastructure and monetize their usage by relying on the
trust relationship with 5G operators. This creates a win-win
situation. There is a big advantage of delegating the device
roaming to 5G operators, which usually have bigger back-end
and have an already established trusted federation to perform
roaming between infrastructures, and in fact, they offer these
kind of services to virtual operators.
III. BACKGROUND
A. LORAWAN
LoRaWAN [3] is a LP-WAN protocol specification that de-
scribes the network protocols to inter-connect wireless net-
work that make use of the LoRa physical wireless interface
[10], which is an scalable bandwidth modulation based on
Chirp Spread Spectrum (CSS).
Figure 1 depicts the most significant characteristics of
LoRaWAN networks (as example of a LP-WAN network) in
contrast to LAN and cellular networks [11].
LoRaWAN is a low cost, high capacity, low power and
long range protocol, that, unlike other LP-WAN technolo-
gies, allows to customize several network options to fine-
tune performance [12], making the network protocol fairly
adaptable. LoRaWAN is an asymmetric protocol, with a star
topology, where devices are connected directly to a gateway,
which in turn, are connected to a LoRaWAN Network Server
(NS) that acts a controller of the network. The standard
defines three kinds of classes according to the three types
of devices capabilities. Class A is intended for constrained
devices, energy-limited devices, with bi-directional commu-
nication but very limited downlink capacity. In Class B the
protocol defines an scheduling mechanism for devices to
receive improved downlink messages, which imposes addi-
tional energy consumption. Finally, Class C allows keeping
the reception windows open, even when devices are transmit-
ting, in order to achieve low-latency communications.
Regarding LoRaWAN security, the protocol defines two
device activation methods LoRaWAN Over-The-Air Activa-
tion (OTAA) and Activation By Personalisation (ABP). In the
ABP mode, either the manufacturer or the application man-
ager adds the cryptography keys in the end-devices and the
Network Server. On the other hand, in OTAA activation mode
(LoRaWAN 1.1), the keys are generated through exchange
of join messages (join-accept and join-request) between the
device, the NS and the Join Server, as shown in steps 1 and
2 of figure 2. The Message Integrity Code (MIC) in the
join-request allows authenticating the device, as the MI C
is generated making use of the device root key NwkKey.
In particular, the function to calculate MI C value for the
JoinRequest header field is:
cmac =aes128_cmac(N wkKey , MH DR|JoinEU I|
DevE U I |DevNonce)
MIC =cmac[0..3]
Then, the device derives the session keys (F N wkS IntK ey,
SN wkSIntKey and N wkS EncKey), with aes-128, us-
ing as baseline the predefined NwkKey root keys, while
AppSK ey is derived using AppKey root key. All the deriva-
tion functions also use the information exchanged in the join
messages, including the DevN once and the JoinN once and
JoinEU I both generated by the Join Server.
The F N wkS IntK ey is used to generate the MI C of
uplink messages, SN wkSIntKey is employed to generate
downlink MIC s, and N wkSEncK ey is used to encrypt
the MAC payloads between the device and the NS using
AES-128. AES-CMAC (Cipher-based Message Authentica-
tion Code) is used to generate the MIC and provide integrity
and authentication. In addition, LoRaWAN features another
channel protection capability at application layer, over the
LoRaWAN NS. In this sense, the AppKey (plus join material)
is used to derive the Application session Key AppSKey
that is used to encrypt and decrypt the application payloads
between the device and the application server (AS).
For further analysis on LoRaWAN security and associated
issues, the reader is referred to this paper [13].
As it will be seen in the following section, that reviews
the 5G authentication and authorizations mechanism, the Lo-
RaWAN security architecture is not ready for its integration
with the extensible Authentication services that are provided
by the 5G network to provide connectivity with other radio
interfaces, e.g. WiFi Calls.
Regarding LoRaWAN roaming, LoRaWAN back-end
specification [14] defines passive and handover roaming
mechanisms to manage the movement of the LoRaWAN end-
device between different Network Servers, being a require-
ment that each operator are configured with a roaming policy
agreement that can individually allow/disallow the roaming
with other network operators identified by their NetIDs.
B. 5G NETWORK
5G Networks are cellular networks based on 3GPP release 15
specification [15] that includes the complete definition of all
the architectural components, interfaces and protocols of the
cellular infrastructure. From 3GPP release 13 it also provides
support for IoT devices using the both LTE-M and NB-IoT
specifications. LTE-M is the simplified industry term for the
VOLUME 4, 2016 3
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
Gateways
Network
Servers
Application
Servers
Devices
gNBs
(RRH)
Core
Network
Devices
LP-WANs
(LoRaWAN) 5G Cellular Network
EDGE
(BBU)
AMF SMF UPF
NSSF NRF PCF UDM
5-20 km
Max range 5-10km
Max range
Data rate: 50 kbps
Maximum payload: 243 bytes
Authentication: AES-CMAC
Encryption: AES-128
Data rate: 200 kbps (NB-IoT) - 1000 (LTE-M) kbps
Maximum payload: 1600 bytes
Authentication: milenage
Encryption: milenage
FIGURE 1. LPWAN vs 5G cellular networks overview
Gateways Network
Servers Application
Servers
Join Server
LoRaWAN App Encryption
* aes-ccm (using AppSkey)
LoRaWAN Network Encryption
* aes-ccm(using NwkSEncKey)
* MIC-uplink=aes-cmac (using FNwKSIntkey)
* MIC-downlink=aes-cmac (using SNwKSIntkey)
1.- joinRequest (JoinEUI, DevEUI, DevNonce)
MIC=aes_cmac(NwKey, MHDR, JoinEUI, DevEUI | DevNonce
2.- joinAccept (JoinNonce, DevAddr, HomeNet-ID, DLSettings )
MIC=aes128-cmac(NwkKey, MHDR, JoinNonce, netID, DevAddr, DLSettings, RxDelay, CF-List)
NwKey, AppKey, DevEUI
AppSkey
NwkSEncKey
AppSkey
3.- Key-Derivation:
FNwkSIntKey = aes128_encrypt(NwkKey, 0x01 | JoinNonce | JoinEUI | DevNonce | pad16 )
SNwkSIntKey = aes128_encrypt(NwkKey, 0x03 | JoinNonce | JoinEUI | DevNonce | pad16)
NwkSEncKey = aes128_encrypt(NwkKey, 0x04 | JoinNonce | JoinEUI | DevNonce | pad16)
AppSKey = aes128_encrypt(AppKey, 0x02 | JoinNonce | JoinEUI | DevNonce | pad16)
NwkSEncKey
AppSkey
Devices
4.- uplink and downlink encrypted messages
NwkSEncKey
FIGURE 2. LoRaWAN: Security scheme Overview
LTE-MTC (Machine Type Communication) low power wide
area network (LP-WAN). Narrowband Internet of Things
(NB-IoT) is also defined in the same specification (rel 13)
as a LP-WAN that focuses specifically on indoor coverage,
low cost, long battery life, and high connection density. It
uses OFDM modulation for downlink communication and
SC-FDMA for uplink communications.
The 5G radio interface is an asymmetric protocol, with
a star topology, where devices are connected directly to a
Distributed Unit (DU) acting as a transceiver for the radio
signals, which in turn, are connected to a (Centralized Unit)
that acts a controller of the radio interface. The infrastructure
is connected to the Evolved Packet Core, clearly separating
the data links and control links. The User Plane Forwarder
(UPF) is the component that received all the traffic of the
final users in order to direct it to the internet or back to
other users of the network. In the control plane, the access
and mobility management function (AMF) is in charge of
dealing with the mobility of the session along the different
handovers of the user. The session management function
(SMF) is in charge of maintaining the existing sessions. Also,
the authentication server function (AUSF) is in charge of
performing the authentication of the users on the network.
The reader can see an overview of a 5G network layer on
Figure 8.
5G networks, through the 5G Core (5GC) can intercon-
nect and/or interwork when users roaming onto a network
different to their Home Public Mobile Network (HPMN).
This will be applicable when New Radio or eLTE (evolved
LTE) radio bearers are used, connected to a 5GC, and both
UE and visited PMN have matching capabilities. In the world
of cellular networks, such as 5G and 4G, the term roaming
is usually associated with the mobility of a device between
countries, but this does not necessarily have to be the case,
and roaming may simply mean the change from a home
domain to a new visited domain. More details about 5G
roaming technical guidelines are detailed in [16].
With respect to 5G security, authentication in the network
is carried out using both an identity and a cryptography
key [17]. About identification, a SUPI is a 5G globally unique
Subscription Permanent Identifier (SUPI) allocated to each
4VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
subscriber and defined in 3GPP specification TS 23.501 [18].
The SUPI value is provisioned in USIM and UDM function
in 5G Core. A Valid SUPI can be either of the following, an
IMSI (International Mobile Subscriber Identifier) or a NAI
(Network Access Identifier) as defined in RFC 4282 [19]
based user identification as defined in TS 23.003 [20] for
non-3GPP RAT. The IMSI (International Mobile Subscriber
Identity) is a unique identification of the subscriber associ-
ated with all GSM, UMTS and LTE, 5G network SIM cards.
It is stored as a 64 bits field and is sent by the phone to the
network. IMSI consists of three parts:
MCC - Mobile Country Code, first three digits. MCC
uniquely identifies the mobile subscriber’s home coun-
try.
MNC - Mobile Network Code, 2 digits (European stan-
dard) or three digits (North American standard). The
length of the MNC depends on the value of the MCC.
MSIN - the remaining digits are the Mobile Subscrip-
tion Identification Number (MSIN) within the network’s
customer base.
SUPI should not be transferred in clear text over 5G
RAN except routing information, e.g. Mobile Country Code
(MCC) and Mobile Network Code (MNC). Therefore, in
many cases it is used a one-time use subscription identi-
fier, called The SUbscription Concealed Identifier (SUCI),
which contains the concealed subscription identifier, e.g. the
MSIN part of SUPI, and additional non-concealed informa-
tion needed for home network routing and protection scheme
usage. Based on home operator’s decision, indicated by the
USIM, the calculation of the SUCI shall be performed either
by the USIM or by the ME
The Authentication key (Ki). The Kiis a 128-bit value
used in authenticating the SIMs on a GSM mobile network
(for USIM networks - 5G and 4G - you still need Kibut
other parameters are also needed). Each SIM holds a unique
Kiassigned to it by the operator during the personalisation
process. The Kiis also stored in the Unified Data Manage-
ment (UDM)) on the carrier’s network.
The USIM card is designed to prevent someone from
getting the Kiby using the smart-card interface. To do so,
the USIM card provides a function that run the authentication
algorithm to sign the data passed by the phone using the
Ki. This, by design, makes using the USIM card mandatory
unless the Kican be extracted from the USIM card, or the
carrier is willing to reveal the Ki.
The authentication process is described in a simplified way
as follows:
1) When the mobile equipment starts up, it obtains the
SUPI/IMSI from the USIM card, and passes this to the
AUSF via AMF, requesting access and authentication.
The mobile equipment may have to pass a PIN to the
USIM card before the SIM card reveals this informa-
tion.
2) AUSF searches then its UDM database for the incom-
ing IMSI and its associated Ki.
3) The UDM then generates a random number (RAND,
which is a nonce) and the AUTN token and signs both
with the Kiassociated with the SUPI/IMSI (and stored
on the SIM card), computing another number, that is
split into the Signed Response 1 (SRES, 32 bits) and
the encryption key CK (64 bits).
4) The AUSF receives UDM authentication vector and
then sends the RAND and the AUTN to the mobile
equipment, which passes them to the USIM card. The
SIM card checks the AUTN token and the SQN number
encoded inside, and if it is right, produces the RES
value and CK using to sign the Ki. It stores them and
passes RES to AUSF.
5) The AUSF then compares its computed SRES with the
computed RES that the mobile equipment returned.
If the two numbers match, the SIM is authenticated
and the mobile equipment is granted access to the
operator’s network. CK is used to encrypt all further
communications between the mobile equipment and
the network.
In [21] authors review the 5G authentication and autho-
rization mechanism as well as associated security issues and
recommendations.
IV. RELATED WORK
Roaming in LoRaWAN allows exchanging information
among different LoRaWAN networks, but it is not yet a suc-
cess as it is a peer to peer roaming mechanism, that requires
high number of bilateral contracts between private-public Lo-
RaWAN deployments, which makes it cumbersome to build
trust. LoRaWAN alliance proposes a centralized roaming hub
that allows scaling, but its feasibility is uncertain, as everyone
needs to blindly trust within that central authority, and in
turn, implicitly trust the members of the hub, in addition the
contract agreements becomes more complex. Relying on 5G
networks and their established telco agreements for cross-
domain handover roaming in LoRaWAN, can facilitate the
trustworthiness matters.
As it is highlighted in this important survey [22] on 5G
Networks for the IoT, a major challenge in machine-type
communications (MTC) (everything, anywhere and at any-
time) is the seamless end-to-end interoperability between the
different IoT radio network technologies used by heteroge-
neous IoT devices.
In [23] authors propose a integration of LoRaWAN with
4G/5G mobile networks, where the LoRaWAN gateway is
modified to act as combination of User Equipment (UE) and
eNB to interact with the Evolved Packet Core (EPC) in the
Cellular network. Therefore, the User dataplane includes the
EPC between the LoRaWAN Gateway and the LoRaWAN
Network Server. Thus, the 5G networks acts as a transport
mechanism to transmit LoRaWAN packets. Unlike in that
paper, our approach does not require every LoRaWAN packet
in the dataplane to go through the 5G Cellular network. In
addition, that proposal does not allow to establish roaming
VOLUME 4, 2016 5
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
connectivity of LoRaWAN devices in visited LoRaWAN
networks, as proposed in our work.
In [24], authors identifies 4 different ways of integrating
LoRaWAN in 5G networks: 1) 3GPP access connectivity in
the LoRaWAN Gateway, i.e. LPWAN packets added to LTE
traffic, 2) LPWAN packets added to WiFi traffic, 3) eNB inte-
gration (LPWAN packets added to users’ traffic), 4) external
(LPWAN traffic does not affect EPC core network). However,
none of these modes addresses the challenge of roaming
in LoRaWAN, and therefore does not allow seamless con-
nection of LoRaWAN devices in other foreign domains by
relying on the 5G network, as it is done in our proposal.
Neumann et al. [25] proposed different models for the
integration of 5G networks in industrial networks such as
IEEE Time-Sensitive Networking (TSN) 802.1. On the other
hand, 5G in 3G-ppp release 15 [15] supports non-3GPP
access (WIFi) to the 5G Core. It supports access-agnostic
authentication. In Non-3GPP access, during network regis-
tration the UE uses an N3IWF (instead of a Cellular gNB),
and establishes a IPsec Security Association (SA) using
IKE and EAP. The N3iWF acts as a EAP Proxy between
UE and AUSF (Authentication Server Function). The UE
performs the EAP-AKA’ [26] authentication that ends-up
with a session key for the tunnels. The N2 interface defines
the control plane signalling between the access network
and the 5GCN. Later on, the N3IWF uses N3 tunnels for
transmitting user-plane PDUs towards the UPF (User Plane
Function). However, our solution is not intended to use the
5G user plane to transmit the LoRaWAN packets, but rather
it defines the authentication procedures that allow the usage
of 5G authentication mechanism as baseline for LoRaWAN
join procedures, where the IoT user datapath is thereafter
transmitted through the LoRaWAN network. In addition,
3GPP release 16 might integrate WLAN systems in 5G using
a "trusted model" called Trusted WLAN Access Network
(TNAN), where the WIFI might be managed by a third-party
trusted by the 5G operator.
An authentication service aimed to achieve interoperability
among heterogeneous LP-WANs is proposed in [27]. The
solution is independent of the type of LP-WAN technology
and integrates the usage of AAA infrastructures and the
Extensible Authentication Protocol (EAP) over CoAp in
order to enable cross domain authentications. The solution
generates corresponding LoRaWAN key material after suc-
cessfully EAP authentication. Nonetheless, unlike our work,
they do not consider the usage of the 5G network (and its
AAA mechanisms) as enabler for handover roaming in LP-
WAN networks.
This paper is the first novel work that takes advantage of
the already existing mobility and roaming capabilities and
trust established in 5G network in order to enable world-wide
hand-over roaming across LoRaWAN networks. Enabling
universal roaming in LoRaWAN would increase device pro-
visioning across networks, permitting valuable use cases such
as location of end-devices across different networks.
V. PROPOSED LORAWAN-5G INTEGRATION
APPROACHES
There are different architectural approaches to perform the
integration between LoRaWAN and 5G networks. They are
determined by physical decisions (deployments, connectiv-
ity), logical decisions (APIs and Interfaces) and by trust re-
lationships and administrative agreements between different
domains. These scenarios enable new possibilities to develop
future IoT applications.
The proposed scenario considers a LoRaWAN device that
is deployed in a visited LoRaWAN network where there is
no roaming agreement with its home LoRaWAN network. In
the current scenario, the LoRaWAN device will not simply
be able to connect into the visited LoRaWAN Network. To
address this challenge, authors propose to use an alternative
interface that integrated the LoRaWAN architecture to the 5G
architecture to carry out the authentication of the LoRaWAN
device using the 5G infrastructure as a common trusted entity
to get access to the network.
As seen in Section III-A, LoRaWAN back-end specifi-
cation [14] defines different roaming solutions to manage
the movement of the LoRaWAN end-device from different
known domains, being a requirement that each operator are
configured with a roaming policy that can individually al-
low/disallow the roaming with other network operators iden-
tified by their NetIDs. Large telecommunication companies
behind 5G, such as Orange and Swisscom [28] [29], among
others, are also involved in other kind of non-cellular net-
works, infrastructures and services, and LoRaWAN is a clear
example of IoT coverage being supported by them. In this
scenario, it could be easy to take advance of their positioning
to allow the simplification in the configuration of roaming not
only among their different networking technologies but also
between a very large number of small LoRaWAN networks
by making use of the existing federation agreements that are
currently available in their global cellular support.
A. GENERAL ARCHITECTURE
The proposed architecture integrates 5G and LoRaWAN
architectures with the aim of achieving interoperability to
provide support for roaming across different LoRaWAN
networks thanks to the authentications and authorizations
mechanisms provided by the 5G networks. To do so, it is
proposed a new interface (and its API) between the Join
Server in charge of the authentication and authorization of
LoRaWAN devices and the UDM server used for the same
purpose for 5G devices. The final objective is to delegate the
LoRaWAN device authentication and authorization to the 5G
infrastructure, which can validate the device’s 5G credentials
and make use of the answer to perform the decision on
LoRaWAN networks.
Figure 3 depicts a multi-RAT IoT device with two different
interfaces: 5G (named User Equipment - UE) and LoRaWAN
(End Device - ED). The IoT device is moved from its home
LoRaWAN network to a new visited network, where there
6VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
1. IoT
Device
AUSF / MME UDM / HSS
NS JS
AS
4G / 5G Network
LoRa Network
NS JS
Visited Domain
Home Domain
UE
ED
gNB / AMF
Lora GW
Visited
IoT
Device
UE
ED
Lora GW
Approach A
Approach B
FIGURE 3. Integrated proposed architecture.
is not any existing roaming agreement. In a normal IoT
scenario, the device would lose LoRaWAN connectivity.
The two approaches (apart from the already existing Lo-
RaWAN roaming capabilities) have been proposed to allow
the device to connect to the visited LoRaWAN network. On
the one hand, the first approach considers that the visiting
device has already an established and existing 5G session,
implying the existence of 5G coverage. In such a case, the
cryptographic session material (session keys) can be accessed
and used by the IoT device to sign and protect LoRaWAN
messages. It simplifies the integration and implementation of
the solution.
On the other hand, the second approach considers that
there is not any existing 5G session either because the in-
terface is disabled to save energy or because there is a lack
in the coverage of the 5G network. In such a case, the IoT
device has only access to the 5G credentials available in the
USIM: SUPI identifier and cryptographic functions. In this
case, the integration between both network architectures is
more complex and will require the modifications of some
LoRaWAN messages. Both proposals are explained in detail
in the following subsections.
B. APPROACH A: LORAWAN INTEGRATION WITH 5G
AUTHENTICATION SERVICES
This proposal assumes that a multi-RAT IoT device with a
dual-interface, LoRaWAN and 5G connectivity is deployed
in a visited LoRaWAN with no LoRaWAN roaming agree-
ments. The IoT device does not have 5G coverage in its radio
interface but it have access to the information and functions
available in the USIM using by such cellular interface. In
this context, the IoT device can make use of the existing
5G credentials available in the USIM to authenticate the
IoT device using the LoRaWAN connectivity in order to be
authorized and accounted into such LoRaWAN network. As
previously described in section III-A, the LoRaWAN specifi-
cation performs device authentication based on a pre-shared
key that is used to calculate the MIC field (a hash field in the
message header) included in every sent LoRaWAN packet
but specially in the initial JoinRequest message. This mes-
sage is used to authenticate the LoRaWAN device, without
any other initial negotiation or processing of any challenge
data from the infrastructure. This implies a great change
USIM 1 (USIM Initial state)
Has: Ki, SUPI, SQN_UE
USIM 2 (UDM Initial State)
Has: Ki, SUPI, SQN_HN
Generates: RAND, AUTH, XRES, CK+IK
USIM 3 (USIM RES generation)
Has: Ki, SUPI, SQN_EU, RAND, AUTH
Generates: SQN_EU', AUTS (sync failure)
USIM 4 (UDM SQN re-sync)
Has: Ki, SUPI, RAND, AUTS, SQN_UE'
Generates: AUTH_2, RES_2/XRES_2, CK_2+IK_2
FIGURE 4. State diagram of 5G authentication key derivation at the USIM.
compared to the authentication workflow carried out in 5G
and other common authentication mechanisms.
When the IoT device trying to authentication using its Lo-
RaWAN cryptographic information into the visited network,
it will fail since there is not any roaming relationship between
the LoRaWAN device and the new visited LoRaWAN net-
work. At this moment, we do propose to do not fail and stop,
and rather, try the LoRaWAN authentication based on 5G
credential. For this aim, authors propose two key innovations.
First, to make use of the USIM authentication information
in the LoRaWAN network and to extend the join server to
allow the delegation of the authentication into the 5G infras-
tructure, thanks to a trust relationship established between
the LoRaWAN network and the 5G network operator. This
trust relationship will allow to make use of the UDM 5G
services to carry out the authentication and use the response
to perform the validation of the first LoRaWAN message
(JoinRequest).
In the 5G-AKA authentication [15], session keys are de-
rived from a pre-shared key (Ki) and some data (RAND,
AU T N ) received from the infrastructure during the au-
thentication process. The 5G cryptographic information and
authentication vectors are calculated in both USIM and in
the UDM service available in the 5G infrastructure but all the
authentication process is initiated and enforced by the AUSF
server. Thus, architecturally, the interface between networks
has been designed via AUSF component but the security
steps are logically done between USIM and UDM.
VOLUME 4, 2016 7
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
Preamble PHDR PHDR_CRC PHYPayload CRC
MHDR JoinRequest body MIC
JoinEUI 5G_SUPI (DevEUI) NonceEUI
Radio PHY layer:
PHYPayload:
JoinRequest body:
5G_RAND 5G_AUTS 5G_RES
FIGURE 5. Extended Join Request frame to contain 5G authentication data.
Figure 4 depicts what are the initial data owned by each en-
tity and what data is interchanged and generated at each step
of the complete authentication steps. At the beginning, UDM
generated RAN D,AU T N ,XRES and C K +IK keys
(see step 2 in Figure 4). It sends both RAN D and AU T N
to the USIM as a challenge. The USIM then generated
directly RES ,CK +IK using such received information, it
allows to authenticate they network by the SIM card. Then,
RES is sent back to the UDM and if it matches with its
calculated XRES, authentication of the UE in the network
will be positive and they have the session keys (CK and
IK already shared), used as encryption and integrity keys,
respectively. (see step 4 in Figure 4). The USIM can be or not
synchronized with the infrastructure with respect to sequence
numbers (SQN ), i.e. S QN _U E is equal to S QN _H N . The
AU T S value is used as a standardized inter-medium step to
perform such synchronization of sequence numbers. Thus,
to make sure both are synchronized, they can decide to share
such AU T S value rather than their sequence number to avoid
replay attacks and at the same time avoid any synchronization
problem. (see step 3 in Figure 4). After the synchronization,
the normal authentication process explained is re-executed.
The proposed solution consists on generating all the 5G
authentication information inside the USIM, even some part
that is traditionally carried out in the network, including the
synchronization steps, to make sure that USIM and UDM
service could share the same cryptography information. From
all the steps previous described, the minimum required pa-
rameters to allow UDM to validate the process carried out by
the USIM and therefore authenticate the device are RAND,
AU T S and RES .RES will be used as a proof of key
possession, RAN D will be used as a shared seed for the
challenge and AU T S will be used to ensure synchroniza-
tion. Our proposal is to send this information inside of the
initial LoRaWAN JoinRequest message. It implies extending
the fields included in the LoRaWAN JoinRequest message
with such fields, RAN D,AU T S and RES as depicted in
Figure 5 and to make the calculation of the MIC value using
the approach of the standard method but including as well
these newly inserted values.
Figure 6 shows a detailed sequence diagram of all the
interactions proposed in this integration approach. Message
1 shows how initially the IoT device tries to access with
a normal LoRaWAN JoinRequest message, but since it is a
visited LoRaWAN network and the LoRaWAN device is not
registered, these message are discarded. After several retries,
the new 5G-LoRaWAN roaming mechanisms is activated.
Messages 2 to 3 are carried out inside the IoT device
between the LoRaWAN device and the 5G USIM component
to generate all required 5G keys and data explained in the
previous paragraphs (Figure 4), as result of the emulation
of the whole information exchanged and generated in the
standard authentication process. At this point, CK and I K
are keep as session keys in the USIM. After that, step 4
generates the LoRaWAN M IC making use of the IK key
as LoRaWAN Network Key. Message 5 and 6 represents the
new LoRaWAN JoinRequest extended to include RAND,
AU T S and RE S fields along with the standard fields, and
newly calculated MIC .
cmac =aes128_cmac(N wkKey , MH DR|JoinEU I|
DevE U I |DevNonce|RAN D|AU T S |RES)
MIC0=cmac[0..3]
When this message is received by the LoRaWAN Join
Server (JS), it has to check the DevEU I as it would be a
normal LoRaWAN message to check if it belongs to a reg-
istered LoRaWAN device. If it is not, before discarding the
message, which is what will happen in a normal LoRaWAN
network, the LoRaWAN NS can checks if the JoinRequest
contains the extra RAND,AU T S and RES fields. These
fields could be ciphered by the USIM using the Kikey, thus
they only could be decrypted by the UDM, which is the other
entity that shares the shared key and the entity responsible for
validating them. It is worth to mention that the LoRaWAN
specification identifies the type of LoRaWAN messages by
using the M T ype field of the M HDR header available in the
LoRaWAN message. We propose to make use of the reserved
bits to allow the LoRaWAN JS to identify if it is a normal
JoinRequest or an extended 5G authentication request. If it
is the second one, it has to process the package as a 5G-
LoRaWAN roaming message. In such a case, first the JS
check the DevN once to make sure the JS is protected against
reply attacks. After that, the JoinRequest that contains the 5G
SUPI identifier in the place of DevEUI field is processed so
that the JS can check if the SUPI corresponds to both valid
Mobile Country Code (MCC) and Mobile Network Code
(MNC). These two values available inside of the S U P A
will allow the JS to identify what 5G network operator this
device belongs to. Then, the JS will see in its configuration
file if there is a trust relationship with such 5G operator. If
it is the case, it will contact such operator. But even if it
is not the case, the JS can either reject the request or ask
a predefined trusted 5G operator. Both cases will be treated
equally but the second one will perform the authentication of
the 5G credentials using the globally standardized roaming
capabilities of the 3G, 4G and 5G networks. In any case,
the information available in the JoinRequest received by
the Join Server and sent to 5G AUSF back-end using a
secure channel. To be concrete, we are using the standardized
diameter protocol (S6a interface), which is the same interface
8VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
IoT Device
LoRa Infrastructure
5G Infrastructure
USIM
LoRa component
LoRa component
Network Server
(Visited)
Network Server
(Visited)
Join Server
(Visited)
Join Server
(Visited)
Application Server
(Home)
Application Server
(Home)
UDM
UDM
Trying standard LoRA authentication
(
1
)
JoinRequest (MIC, DevEUI,
JoinEUI_A, DevNonce)
Join failure (DevEUI not recognised by NS, messages dropped by the NS)
Trying LoRa authentication using 5G credentials
Using SUPI/IMSI as user ID. Trying with
dierent JoinEUI (from a list of valid JoinEUIs)
(
2
)
5G_AV_generation_req()
(
3
)
5G_AV_response (RAND,
AUTS, RES, CK, IK)
(
4
)
gen_MIC (IK, MHDR | JoinEUI_B | SUPI
| DevNonce | RAND | AUTS | RES)
(
5
)
Join-Request (MHDR | JoinEUI_B | SUPI
| DevNonce | RAND | AUTS | RES | MIC)
(
6
)
JoinReq (JoinEUI_B | SUPI | DevNonce
| RAND | AUTS | RES | MIC)
check DevNonce against replay attacks
Diameter / S6a Interface
(
7
)
Request_AuthN_Vectors (SUPI, RAND, AUTS)
(
8
)
Response_AV (XRES, CK, IK)
RES vs XRES verication using
cryptographic info derived from
Join message and Ki
check MiC against IK
Derivation of LoRa session keys using 5G CK as NwkKey
(
9
)
JoinAns (LoRa_session_Keys)
LoRa join accepted
(
10
)
Join-accept (AppNonce, NetID,
DevAddr, RxDelay, CFList)
LoRa session keys derivation using 5G CK as NwkKey
(
11
)
data
(
12
)
data + AppSKey
FIGURE 6. Proposed Flow diagram of LoRaWAN authentication using only 5G credentials (Approach A).
being using in the 5G back-end. Messages 7 and 8 shows such
message interchange. To carry out this exchange, it has been
necessary to define two new messages to consult the UDM,
a Request Authentication Vector message (8) that include the
params required by the UDM to carry out the authentication
of the user in the network SU P I ,RAND,AU T S and the
Response AV (Authentication Vector) message (9) to obtain
the answer with the RAN D,X RES,AU T N ,CK and IK
fields. When message 8 is received in the UDM, the standard
authentication protocol is used with the only exception that
traditional the RAN D value is generated by the UDM , and
in this case it is provided as parameter to the UDM . The
answer does not requires to send the AU T N and RAN D to
the JS so that only XRES ,CK and IK and sent back to
the JS to minimize the exposure of information.
The JoinRequest MIC field is used to authenticate and
validate the message. It is kept in the JS without being sent
to the UDM service until the response obtained from the
UDM is received. If the RES generated by the IoT and
available in the JoinRequest matches the value provided by
the UDM in the XRES field, then it is proved on the one
hand that the 5G user is who claims to be and knows the
corresponding 5G CK and I K sessions key. At this moment,
the JS knows both CK and I K session keys and can use the
IK to perform the validation of the MIC. It will prove also
to the JS the possession of a secure key to be used in the
LoRaWAN Network to encrypt messages. Notice that at this
state, it has been decided to add an extra layer of security over
the existing LoRaWAN security but not making use of such
IK and instead make use of the other 5G key CK to encrypt
any further messages. Thus, the approach is to make use of
the CK as LoRaWAN Network Key. This will also validate
that the algorithm generated is 5G compliant.
Message 9 contains the answer from the JS to the NS
with the session keys (CK as N wkKey). At this point the
JoinRequest is accepted and the IoT device’s security net-
VOLUME 4, 2016 9
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
work data are generated by the NS using standard LoRaWAN
security. To be concrete, the device derives the session keys
(F N wkS IntK ey,SN wkSIntKey and N wkSEncKey),
with aes-128, using as baseline the predefined NwkK ey
root keys. The network does the same and includes other
data such as NetID,DevAddr,AppN once,RxDelay and
CF List, which are transmitted to the LoRaWAN device
using the JoinAccept message (10). Finally, messages 11
show the IoT device successfully having access to the vis-
ited LoRaWAN network thanks to the architecture proposed.
However, when the data arrives to the NS, it faces another
challenge that need to be addressed. The packet needs to react
the appropriate application server into the home network. To
address this challenge and take the profit that the 8-bytes
JoinEU I field follows a hierarchical addressing using IEEE
EUI64 specification. We propose to make use of the 4 first
bytes to encode the destination IP address of the Application
Server whereas the other 4 last bytes are used to identify
uniquely such application inside of the server. This way
packets will arrive to the home Application Server encrypted
using the associated key and thus they can be decoded and
processed accordingly.
C. APPROACH B: NON STAND ALONE LORA-5G
CONNECTIVITY
The starting point for this use case is an IoT device with
both interfaces LoRaWAN and 5G that has moved to or
been deployed at a new/visited LoRaWAN network where
there is not LoRaWAN roaming agreements between the
visited network and the home LoRaWAN network. The IoT
device has also a 5G interface available, which is running and
connected to its 5G network. Authors propose to use the 5G
credentials and the session keys derived from the active 5G
connection to authenticate the device through the LoRaWAN
network against the 5G back-end infrastructure.
This proposal offers a simpler integration but imposes
stronger requirements such as the dual coverage of both 5G
and LoRaWAN at the moment of the authentication in the
network. The sequential steps involved in this use case look
similar to those presented in the previous section, but in fact,
are significantly different in their design.
Figure 7 depicted the sequence diagram of this use case.
The first message represents the exchange made between the
IoT device through its 5G interface and the 5G infrastructure,
to obtain connectivity using the standard attach and connect
mechanisms, that allow to establish an active session between
the device and the 5G network.
After the successful authentication in the 5G network, the
IoT device tries to connect to a visited LoRaWAN network
(Message 2), and the device does not have a valid LoRaWAN
credential for that network. This entails an authentication
failure, since the device is not recognized by the visited
network and there are no roaming agreements between the
visited LoRaWAN network and the home network. Then, the
hybrid roaming authentication is activated to make use of 5G
credentials and session cryptographic material to authenticate
the IoT device into the LoRaWAN network.
In this approach, the usage of the USIM functionalities is
significantly reduced with respect to approach A to almost
their standard use. Hence, the USIM and 5G network are
already synchronized due the existing session. Second, there
is no need to generate both RAN D and AU T N in the
USIM for authentication purposes and there is also no need
to generate AU T S for synchronization purposes. It makes
messages 3 and 4 now much more simplified with respect to
the previous approach. To be concrete, Messages 3 and 4 are
sent internally between the IoT device the USIM to obtain
the 5G identifier (SUPI/IMSI/SUCI) and the cryptographic
information (session keys - CK and I K). As seen above,
the authentication of a LoRaWAN device is done through the
validation of the MIC field of the LoRaWAN JoinRequest
message header, generated in step 5. Now, the format of this
JoinRequest is fully compliant with the standard one since
there is not any need to pass any extra RAND,AU T S and
RES information in the message due to the existing 5G
session.
The calculation of the MIC is also following the stan-
dard procedure with the only difference that it is making
use of the 5G IK as a key to perform the generation of
the MIC instead of the original LoRaWAN N wkKey. It
makes a significantly easier integration. The standard Lo-
RaWAN JoinRequest have three fields: DevEU I,JoinEU I
and DevN once. It is necessary to replace the LoRaWAN
DevE U I identifier with the S UP I , which internally have
a specific format and allows to recognize that identifier as a
5G own one and it will allow to activate the roaming as well
as subsequently resend the package to the corresponding 5G
back-end.
The logic of the LoRaWAN JS is exactly the same as the
one indicated in the previous use case (messages 6 and 7)
but Message 7 and 8 that imply the interaction with the 5G
architecture are different. Now, the AUSF and UDM have
already done a standard 5G authentication. It implies that
AUSF have in memory both CK and IK from the authen-
tication vector received by UDM. Therefore, we propose the
addition of a new method in the API of the AUSF called:
Request_LoRaAuthN , accessible through the S1AP NAS
interface, that receives all the information available in the
JoinRequest that is required to create the XM I C (M I C
generated by AUSF) together with the MI C value available
in the JoinRequest. Then, AUSF will make use of the I K to
perform the creation of such XMIC. As a result, if they both
matches, means that both ends of the communication have
a proof of possession of the IK. Only if there is a match,
Message 10 returns the XMIC,C K and I K to the join
server. This will allow the Join Server to check the XMIC
against the MIC received in the JoinRequest. Notice that
this match has been already done by the AUSF but here the
process is again done since the Join Server needs also to
demonstrate such proof of possession now for the LoRaWAN
network. If they match, then as an extra security layer, the
10 VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
IoT Device
LoRa Infrastructure
5G Infrastructure
USIM
USIM
LoRa component
LoRa component
Network Server
(Visited)
Network Server
(Visited)
Join Server
(Visited)
Join Server
(Visited)
Application Server
(Home)
Application Server
(Home)
AUSF
AUSF
5G authentication
(
1
)
5G Authentication - session established - key derivation
Trying standard LoRA authentication
(
2
)
JoinRequest (MIC, DevEUI,
JoinEUI_A, DevNonce)
Join failure (DevEUI not recognised by NS, messages dropped by the NS)
Trying LoRa authentication using 5G credentials
Using SUPI as user ID. Trying with dierent JoinEUI
(from a list of valid JoinEUIs)
(
3
)
requestSessionKeys ()
(
4
)
answerSessionKeys ()
(
5
)
mic_gen (IK, MHDR | JoinEUI_B
| SUPI | DevNonce)
(
6
)
Join-Request (MHDR | JoinEUI_B
| SUPI | DevNonce | MIC)
(
7
)
JoinReq (MHDR | JoinEUI_B
| SUPI | DevNonce | MIC)
check DevNonce against replay attacks
S1AP Interface
(
8
)
Request_LoRa_AuthN (MHDR
| JoinEUI_B | SUPI | DevNonce | MIC)
(
9
)
generate_XMIC (IK,
MHDR | JoinEUI_B
| SUPI | DevNonce)
MIC vs XMIC verication
(
10
)
Response_LoRa_AuthN (XMIC, Ck, IK)
MIC vs XMIC verication using
cryptographic info derived from
Join message and IK
Derivation of LoRa session keys using 5G CK as NwkKey
(
11
)
JoinAns (LoRa_session_Keys)
LoRa join accepted
(
12
)
Join-accept (AppNonce,
NetID, DevAddr,
RxDelay, CFList)
LoRa session keys derivation using 5G CK as NwkKey
(
13
)
data
(
14
)
data + AppSKey
FIGURE 7. Proposed Flow diagram of LoRaWAN authentication using 5G derived keys (Approach B - 5G pre-authentication)
The rest of the process will be carried out in the same way
as the described in approach A. Notice that this approach
makes use the 5G CK as a LoRaWAN NwkKey, similarly
to the other approach presented. And, the IoT device will
derive session keys (FN wk SI ntKey,S N wkSI ntK ey and
NwkS EncKey), with aes-128, using as baseline the prede-
fined NwkK ey root keys.
D. COMPARATIVE ANALYSIS OF THE PROPOSED
ROAMING APPROACHES
This section provides a comparative analysis of the two
different proposals previously described. A summary of such
comparison is shown in table 1. As the reader can see,
approach B is significantly following almost all the standard
procedures and the only requirements to extend the S1AP
interface with a new functionality to calculate LoRaWAN
MIC using internal cryptography material available by the
AUSF however, the main drawback is the need of the dual
coverage in the moment of the authentication. Approach A
is able to remove such limiting requirement but imposes
a significant deviation of the standards in both LoRaWAN
and 5G networks with the drawbacks imposed in terms of
the adoption by industry, especially in terms of firmware
optimization, hardware feature implementation and software
VOLUME 4, 2016 11
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
APIs. It also required a deeper security analysis, described
later on. For these reasons, authors have decided to carry out
the security analysis for both approaches to ensure correct-
ness of the solution but to perform the empirical validation of
the architecture proposed only on approach B.
Feature Approach AApproach B
Standard LoRaWAN MIC Calculation NO YES
Standard LoRaWAN JoinRequest Message NO YES
Required Dual and Simultaneous NO NO
Coverage Anytime
Required Dual and Simultaneous YES NO
Coverage at Authentication Phase
Standard USIM Cryptography Functions NO YES
Standard s6A Interface NO YES
Standard S1AP Interface YES NO
TABLE 1. Comparison between different approached proposed
VI. SECURITY ANALYSIS OF THE PROPOSED ROAMING
APPROACHES
In this kind of interoperability scenarios in which situations
of integration of protocols, infrastructures and organizations
arise, security can be affected in different aspects. At organi-
zation level, because new trust relationships have to be estab-
lished between the involved organizations. At infrastructural
level, services may require new trust relationships based
on service enrolments, certificates and new interconnection
interfaces. Finally, at the protocol level, interoperability solu-
tions usually require changes at different depths, modifying
the uses of the exchanged messages and the information
transported in them, as well as the definition of new messages
to adapt to the requirements of each case of use.
The designed interoperability solution between Lo-
RaWAN and 5G, has been performed minimizing the changes
in the existing standards. The changes mainly affect client
devices and the infrastructure responsible for authentication,
leaving intact, in most cases, intermediate components in
charge of the exchange of messages in data and control
planes.
The two proposed solutions share common modifications
that can affect different security aspects that must be taken
into account. Next, the changes carried out by the proposed
solutions and the decisions taken to minimize security and
privacy risks are analysed.
A. JOIN-REQUEST AS PLAIN TEXT
LoRaWAN standard authentication is done through the Join-
Request message, which is the first message sent by the Lo-
RaWANdevice to the Network Server in order to establish the
connection and authenticate the device. This message, sent
in clear text, contains mainly the JoinEU I ,DevEUI and
DevN once. These fields, along with others, are processed in
the MIC function to verify the integrity of the message. For
this, the shared secret key NwkK ey is used, which allows
also verifying that whoever generated that MI C results
corresponds to the DevE U I .
Thus, in our approach A, it is also sent in the same
JoinRequest both RAND,AU T S and RES. These fields
are provided with the only purpose of verifying the proof
of possession of Kiand the associated derived CK and
IK keys, which are used then to authenticate such IoT
device. Thus, if a malicious attacker has access to this plain
text message, he cannot perform a reply attack since the
DevN once have been already consumed by the legitimate
request. Besides, if the attacker might want to change such
DevN onve value, then the M IC cannot be recalculated
since he is not in a possession of the IK . Therefore, authors
do not foresee any concern to this approach. However, we
have proposed an extra protection, to encrypt them using the
Kiso that only UDM service can decrypt it. This implies
an enhanced privacy solution where reply attack will not
feasible.
B. SUBSCRIPTION PERMANENT IDENTIFIER (SUPI)
PROTECTION
To identify the 5G user in the LoRaWAN infrastructure,
such 5G SUPI/IMSI identifier needs to be transmitted instead
of the LoRaWAN identifier. It can involve a security and
privacy risk [30] since the SUPI/IMSI is recommended to be
encrypted in 5G even when it is not done in 4G and it will be
exchanged in LoRaWAN network inside of the LoRaWAN
JoinRequest message without encryption. To cope with this
issue, our proposal encrypts the 5G SUPI/IMSI identifier
during the LoRaWAN packets transmissions using the 5G
shared key (Ki).
According to the 5G specification, the SUPI/IMSI iden-
tifier is, in general, never sent in clear text over the radio
5G network, being this feature considered a major security
improvement over prior generations such as 4G. Neverthe-
less, there are certain situations where authentication through
the use of temporary identifiers is not possible. For instance,
when a user registers with a network for the first time and is
not yet assigned a temporary identifier. In this case, and even
more in roaming scenarios, is not possible to use a temporary
identifier.
The mechanism defined by the 5G standard is the use of
the Subscription Concealed Identifier (SUCI). This identifier
is a privacy preserving identifier containing the concealed
SUPI. In 5G, the UE generates SUCI using a ECIES-based
protection scheme with the public key of the Home Network
that was securely provisioned to the USIM during the USIM
registration. Only the MSIN part of the SUPI gets concealed
by the protection scheme while the home network identifier,
the MCC/MNC, gets transmitted in plain text. In the pro-
posed solution, the protected part of SUCI is ciphered using
the 5G shared key (Ki), which only allows the disclosure by
the 5G back-end.
12 VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
These attacks are known as IMSIcatching attacks [31] and
persist in today’s mobile networks 4G LTE/LTE+ [32]. The
use of SUCI is compatible with our both approaches and
aligns the solution to the last security recommendations of
5G specification.
C. MULTIPLE KEYS AS LORAWAN NETWORK KEY
It is worth mentioning that both proposed integration ap-
proaches make use of the stronger security mechanisms
available in 5G to provide an extra layer of security over the
LoRaWAN network. It is done by employing not only one
NwkK ey but using CK and IK as two different NwkK ey.
Thus, IK is used only for the JoinRequest (MIC calcula-
tion) and the CK for any other message and session key
derivations. It enhances significantly the changes to get keys
compromised.
D. MUTUAL AUTHENTICATION
In terms of mutual authentication and trust relationships: i)
IoT device needs to get authenticated in both, the visited
LoRaWAN network (JS) and in 5G network (AUSF/UDM).
ii) JS need to authenticate both, IoT and 5G network. And iii)
5G network need to authenticate both the JS and IoT device.
Regarding mutual authentication IoT-5G, it will make
use of the standard mutual authentication mechanisms for
approach B. In approach A, however, this is carried out by
the generation of the XMIC in the AUSF and its validation
against the MIC provided in the authentication request
received by the JS.
With regard to JS-(UDM/AUSF) mutual authentication
and encryption, this is carried out by the creation of a secure
channel (TLS) where there is a mutual authentication based
on a PKI infrastructure and x.509 certificate in both client
(JS) and server (UDM/AUSF) side. It allows both encryp-
tion of the communications and mutual authentication, using
standard mechanisms.
With respect to IoT-(visited JS) mutual authentication, JS
completely relies on the 5G network to provide a trusted IK
and CK to allow JS to authenticate IoT devices. This trust
relationship is a key aspect of the proposed architectures.
Security is addressed previously with the usage of the mutual
authentication between JS and UDM/AUSF and a secure
channel as previous discussed. IoT device authenticates the
network since messages exchanged thereafter are encrypted
with the NwkS Key session key only known by the NS
that uses it as proof of possession, thereby guarantying that
Network server is trusted.
The implications of this trust relationship between JS and
AUSF/UDM is that JS will allow to pass messages across
its network based on such trust relationship. However, notice
that to allow this to happen, the IoT device and its possession
of the IK and CK need to be successful along the authenti-
cation process.
In the proposed Approach A, RAN D,AU T S and RES
are generated in the USIM so that the USIM has not really
authenticated the 5G infrastructure, but notice that in fact the
IoT device does not plan to connect and maybe does not have
even coverage. Thus, this is not any security concern with
respect to the 5G network.
E. KEYS SHARED BETWEEN AUSF/UDM AND JS
In traditional 5G authentication, the Kiis the master key
provisioned inside of the USIM that never goes out of
the USIM. However, both CK and IK session keys are
transferred to the IoT Device without any mayor security
concerns since the PIN code has been already being used to
authenticate access to such keys. In the information exchange
between AUSF/UDM and JS these keys are also being shared
between. There is not any mayor concern (similarly as with
the USIM approach) to share such keys between them. How-
ever, a mechanism similar to the USIM should be provided
from the infrastructure side. To address this, a dual layered
security mechanism has been proposed. First a PKI-based
secured channel (TLS) with dual authentication in place.
And second, the validation of the MIC received as a initial
proof of possession of the Kiwithout unveiling any further
information. This is the reason why the MIC is passed to
AUSF/UDM so that this validation can be done before to
share any session key with JS. Obviously, the Kiwill never
go outside of the 5G UDM which is what is expected to be,
following standard 5G security architecture.
F. REPLAY AND DDOS ATTACKS
With respect to replay attacks against the standard Lo-
RaWAN architecture, LoRaWAN uses a random number
created by the EDs (DevN once). It is used to circumvent
replay attacks during the authentication phase.
NS keeps the list of used (DevN onces) and auto-
matically protects the network from the re-usage of the
same DevN once. As a result, any DDoS attack using the
same DevN once will also be mitigated. However, an ad-
vanced DDoS could be smart enough to generate a different
DevN once for each JointRequest, then NS will not ignore
such messages and the flooding will be received in the JS
that, in turn, will provide a negative authentication based on
the MIC value and the fact that the attackers do not know
the NwkK ey.
In our approaches, it will also produce an overhead in
AUSF (approach B) or UDM (approach A) even time JS
is being attack. In summary, the amount of traffic that can
be injected in the network for authentication purposes until
the device received a permanent denial is 216being 16 the
number of bits used for the DevN once. After that, it will
be a lack of any non-used DevN once and NS will stop
such DDoS. Thus, the maximum amount of traffic generated
by a malicious traffic is exactly 65536 23 being 23 the
standard size of the JoinRequest, totalling a maximum of
1.5 MBytes. This is a clear method to control this risk,
but authors also propose to have a maximum number of a
configurable roaming access attempt before to stop passing
request to the UDM and AUSF. e.g. 3 times in a minute.
Thus, this is a simple mechanism to be addressed by the NS
VOLUME 4, 2016 13
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
in order to keep the number of JoinRequest received in the
last X seconds from a device and drop any further attempt.
Another aspect to analyse is the reason why AUSF/UDM
will also receive such attack when the JS is being attacked.
The reason is that JS (in roaming) does not have yet any key
to check MIC before to do the request to AUSF/UDM, thus
it needs to pass always such message, but again the attack can
be controlled, as already explained.
VII. IMPLEMENTATION AND VALIDATION
In order to validate the feasibility of the proposed solution, a
Proof of Concept (PoC) implementation has been carried out
focusing on the second approach defined in (Section V-C).
Additional instrumentation has been included to gather met-
rics to perform evaluation.
As explained in Section V-D, Approach B has been cho-
sen for implementation and validation, since it better aligns
with existing standards, requiring only small changes at the
LoRaWAN specification level and minor modifications at the
service adaptation level.
The PoC has been developed using software at production
level such as Mosaic 5G [33] for the 5G infrastructure and
ChirpStack/Broocar [34] for the LoRaWAN infrastructure.
There is not any modifications at the hardware level in any
of the devices involved in the infrastructure, which facilitates
the reproducibility of the tests carried out, explained in more
detail in sections B and C of this section.
Section A describes the testbed where the validation has
been carried out. After that, Section B. provides the pro-
cess that has been carried out to perform the validation of
the approach. Then, Section C. describes the results of the
execution of such validation process. These results include
the execution of each of the steps involved in a complete
execution of authenticating an IoT device with LoRaWAN
and 5G interfaces in accessing a LoRAWAN network using
5G credentials. Finally, Section D provides a detailed analy-
sis of different metrics to evaluate the communication cost,
effectiveness, overhead and viability.
A. IMPLEMENTATION AND TESTBED DESCRIPTION
Figure 8 depicts the whole architecture deployed in our
premises. It is a dual architecture that includes both Lo-
RaWAN and 4G/5G components. Both architectures have
several components that are virtualized and deployed as
Virtual Network Functions (VNFs) in different physical ma-
chines. All the Virtual Machines have been defined with the
same configuration: CPU Intel Core Processor (Broadwell)
64 bits, RAM 2GB, HD 20 GB and Ubuntu 16.04 kernel
4.15.0 low-latency.
With respect to IoT devices, we are using a Pycom Fypi
ESP32 device with WIFI, Bluetooth LoRa, Sigfox, LTE CAT
M1/NB1 interfaces. This device have a SPI interface to the
LoRaWAN interface and a UART interface to the 5G NB-
IoT interface. The firmware v1.17.3.b1 has been customized
including an ad-hoc LoRaWAN client written in micropython
that interacts with the UART NB-IoT interface to connect to
the 5G network and to recover. It uses AT commands over
UART both SUPI/IMSI and session credential information
(CK and I K ) to be used as N wkKey for the LoRaWAN
modem when requested. The micropython API allows to
interact with the USIM at low level, necessary to manage
the access to the cryptographic material. This part has been
made using as baseline the Osmocom [35] open source
libraries [36] [37] that offers both, client and infrastructure
functions very appreciated for our purpose. These credentials
are used to replace the DevE U I and to calculate the M I C
using the IK. The code that interacts with the USIM is based
in the Osmocom libraries [35]
Regarding the LoRaWAN network, the LoRaWAN gate-
way is an standard Raspberry Pi 2 with a IC880 hat to
provide a LoRaWAN interface. It has been installed with
the Chirpstack/Brocaar LoRaWAN Gateway software, the
Packet Forwarder (poly_pkt_fwd). The LoRaWAN NS is
a VNF using in EDGE-1 zone of OpenStack (cloud com-
puting stack), and with Chirpstack/Brocaar LoRaWAN Net-
work Server (bridge) and Mosquitto MQTT v3.1.1. The Lo-
RaWAN AS and JS are both integrated in the same software,
the Chirpstack/Brocaar LoRaWAN Application Server. This
code has been modified to identify roaming messages from
the IoT device and, in case of roaming process, being able to
contact with 5G AUSF component to delegate the validation
of the LoRaWAN JoinRequest message.
Regarding the 5G Networks, the Radio Access Network
has been prototyped using a Ettus URSP B210 SDR running
the UHD firmware v3.9 and Mosaic 5G v1.0 running in a
VNF using EDGE-2 zone of OpenStack. Both AUSF and
UDM has been installed using the NextEPC Core network
components [38] (MME and HSS, respectively) due to the
limitation, that there is not any open source implementation
of a 5G core network available to perform the validation.
However, all these principles are directly applicable to the
new 5G core network. Figure 8 does not show the rest of 5G
components for a shake of simplicity, however, 5 different
VNF are deployed in the CORE of the network with all the
architectural components of the 5G network. Both AUSF/-
MME and UDM/HSS have been modified according to the
approach B presented in previous sections.
B. VALIDATION PROCESS
For the validation of the approach, we have implemented a
proof of concept of the Approach B previously presented,
allowing a FiPy IoT device being authenticated into the
visited LoRaWAN network using the CK and I K session
keys. To allow so, a new micropython API has been im-
plemented that permits extracting the IK nd C K session
keys as well as the SU P I from the IoT device to be used.
The client can access to them after the connection to the
5G network has been carried out and be used as NwkK ey.
Namely, the prototype makes use of the I K for the M I C
calculation of the JoinRequest whereas makes use of the CK
for the LoRaWAN session keys derivation used for the MI C
calculation of the rest of messages.
14 VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
5G
Network
LoRa ChirpStack GW
(IC880 + RPi)
JS + AS VNF
(ChirpStack AS)
LoRaWAN
gNB / AMF VNF
(OpenAir Interface)
UPF VNF
(OpenAir-CN)
AUSF / MME VNF
(OpenAir-CN)
UDM / HSS VNF
(OpenAir-CN)
Visited
LoRaWAN
Network
IoT Device
(Pycom FiPy Board)
4G / 5G
gNB RRH
(USRP B210)
Internet
5G-EDGE-1
5G-CORE-1
LoRa-CORE-1
Network
Physical machine
Virtual machine
Physical connection
Logical flow
New logical flow
NS VNF
(ChirpStack NS)
LoRa-EDGE-1
FIGURE 8. Diagram of the implemented LoRaWAN and 5G integration testbed
The Join Server is the component in charge of validating
the JoinRequest messages. The PoC has been implemented
using the LoRaWAN library offered by Chirpstack/Brocaar.
The modifications have been focused in the LoRaWAN li-
brary, which is in charge of managing and validating Lo-
RaWAN messages such as JoinRequest message. To be con-
crete, it has been modified the case where a unknown DevEUI
is received in a JoinRequest, checking whether the format of
the received identifier matches with the SUPI/IMSI format by
extracting both MNC and MCC and checking them against
a list of pre-configured IP address where the 5G AUSF is
available for such 5G network. It that case, the roaming
protocol is activated sending the request against AUSF. This
has been the most challenging part of the integration. It has
required to perform the extension of the API exposed by the
AUSF/MME in order to offer two new methods in its S1_AP
interface, matching the signature indicated in Figure 7. Al-
though the defined solution maintains the use of the S1AP
interface for the validation of the message received from the
LoRaWAN Join Server, it is necessary not only to implement
the new request-response pair of interactions. Probably the
most complex aspect of this integration has been the creation
of the S1AP client library to interact with the AUSF inside
of the JoinServer. Notice that LoRaWAN implementation is
carried out in GO language whereas 5G implementation is
carried out in C/C++ language.
For demonstration purposes, the implementation of the
AUSF API has intentionally ignored many of the S1AP
checks indicated in the standard and only focused on validat-
ing the approach. Obviously, on production stage, all these
standard checks should be implemented. Upon returning to
the LoRaWAN Join Server, the stored JoinRequest fields are
retrieved and the preceding MI C from the IoT device is
compared with the XMIC provided by the 5G infrastruc-
ture. If they match, the LoRaWAN device is successfully
authenticated and normal LoRaWAN operation proceeds.
C. EXECUTION
In terms of the cryptography used to carry out such au-
thentication, and as a proof of validation, our SIM card
has been intentionally reprogrammed with this cryptography
information generated for this validation purposes.
KI=0x89423C6213B1762E5D96CF 1756E929B D
SUPI=809901700000020498
(0xB3D594E1B7C7812)
Information presented here in is accurate so that it will
allow any reader to reproduce the validity of the approach
B described in this contribution. As a result of the 5G
authentication, it has been generated:
IK = 0xC295253C A52E58BA43228C380C86F EC 1
CK = 0x57B352B81939C178863E63f90EADCB 78
RES = 001fA4d4AC200DAB
Then, LoRaWAN information available in the JoinRequest is
the following:
VOLUME 4, 2016 15
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
MHDR = 0x00 (JoinRequest),
AppEUI = 0x0000000000000001,
DevEUI = 0x00B3D594E1B7C781,
DevNonce = 0x15A1 (randomly generated).
Notice that DevE U I is made with the S UP I identifier in
hexadecimal and with padding to fit into the size of the
field. These field produces the following MIC as an output:
MIC=1E01652E. XMIC produced by AUSF is exactly the
same value validating the feasibility of the presented solu-
tion.
D. VALIDATION ANALYSIS
The execution of the whole authentication process has been
carried out in different scenarios to allow comparison be-
tween them. This process has been instrumented to gather
some key metrics to allow the analysis of the overhead
proposed by our solution. To be concrete, three different
scenarios has been executed, including traditional LoRaWAN
authentication in local networks, and roaming using our ap-
proaches. Table 2 summarises the validation results obtained
along the tests carried out as proof of concept with the aim
of analyse the communication cost and overhead inserted by
the proposed approach.
In terms of overhead, approach A introduces an overload
in the size of Join Request message since it is necessary to
transport three new additional fields (RAND,AU T S and
RES ). This implies an increase of 38 bytes over the standard
message size which is 23 bytes. This increment is not a
problem since the new size is supported by the LoRaWAN
standard. On the other hand, approach B does not have impact
in the size of Join Request message as shown in Table 2.
Additionally, the effect introduced by the delegation on
a third party such as the 5G back-end of the LoRaWAN
authentication process implies a series of additional hops
between components and additional cryptographic calcu-
lations with the consequent delay associated. A standard
LoRaWAN authentication requires four hops to complete
the device authentication process. The proposed solutions
imply an additional access to 5G back-end, adding an extra
request/response exchange, leading to six his required in total
to complete the authentication. It is worth to mention that
approach B required that the authentication of the device
in the 5G network is also previously carried out with an
additional four hops.
To take time measurements between the different pack-
ages, modifications have been made to the LoRaWAN Gate-
way. The measurements are not made in the IoT device itself
since the sending and receiving windows are delimited and
fixed in advance by the LoRaWAN standard. A normal au-
thentication in a home LoRaWAN network takes 10ms in our
setup, whereas it takes 14ms in a visited LoRaWAN network,
which gives an idea of the small overhead introduced in the
control plane, i.e. 4ms. Besides, there is not any additional
overhead in terms performance in the data plane since it has
not been modified.
TABLE 2. Validation results analysis. Joint Request (JR)
Hops Time JR Packet Size
Standard LoRaWAN 4 10 ms 23 B
Aproach A 6 - 61 B
Aproach B 6* 14 ms 23 B
To ensure the low energy and resource consumption re-
quired in IoT networks, the LoRaWAN specification defines
two very short receive windows, aimed to obtain the response
messages each time the device is activated (either to send
an update or register in a new network). In the case of
the JoinRequest authentication message, as defined in Lo-
RAWAN Regional Parameters [39], the maximum delay to
receive the JOIN _AC CEP T is 5-6 seconds. The 4ms of
overhead associated to our approach is minimal compared to
such standard reception windows, which makes the approach
suitable for LoRaWAN standard and does not impose any
additional energy consumption.
VIII. CONCLUSION
This paper has defined the first novel proposal aimed to en-
able handover roaming in LoRaWAN by relying on 5G secu-
rity services. To this aim, two different approaches to achieve
the integration of LoRaWAN and 5G have been exhaustively
detailed, analysed and compared. The first approach, based
on extending LoRaWAN join procedures for piggyback-
ing 5G security material, is intended to allow roaming in
LoRaWAN with 5G authentication. This solution does not
require 5G coverage in the visited LoRaWAN network, but
several modifications in the LoRaWAN and 5G standards
are needed. On the other side, the second approach, based
on exploiting 5G authentication services, has been selected
for implementation and validation, since it follows almost all
the standard procedures with minimal modifications. This ap-
proach has been successfully implemented, with the required
developments for the IoT device (including in the 5G SIM
card part), in the LoRaWAN Join Service as well as in the
5G AUSF to perform the 5G authentication as detailed in
the paper. The implementation, deployment and validation of
the approach in a real integrated LoRaWAN and 5G testbed,
as well as the conducted security analysis has shown the
feasibility of the proposal. As future work, we envisage
to devise additional novel trusted security procedures for
mobility and roaming aimed to cope with interoperability
issues between 5G and other IoT wireless network protocols.
ACKNOWLEDGMENT
This work has been funded by a grant for postdoctoral
training and improvement abroad, funded by the Ministry
of Employment, Universities, Enterprise and Environment of
the CARM (20938/PD/18), through the Seneca Foundation-
Agency for Science and Technology of the Region of Murcia
(Spain). This work has been also partially supported by the
European Commission H2020 5G-PPP ICT-2016-2 SliceNet
16 VOLUME 4, 2016
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
project GA 761913, as well as H2020 European project
INSPIRE-5Gplus GA 871808.
REFERENCES
[1] C. Bockelmann, N. Pratas, H. Nikopour, K. Au, T. Svensson, C. Ste-
fanovic, P. Popovski, and A. Dekorsy, “Massive machine-type communi-
cations in 5g: physical and mac-layer solutions,” IEEE Communications
Magazine, vol. 54, pp. 59–65, Sep. 2016.
[2] EGHAM, “Gartner says 5.8 billion enterprise and automotive iot endpoints
will be in use in 2020,” 2019.
[3] L. A. T. Committee et al., LoRaWAN 1.1 Specification.
[4] J. C. Zuniga and B. Ponsard, “Sigfox system description,” LPWAN@
IETF97, Nov. 14th, vol. 25, 2016.
[5] M. Vaezi, Z. Ding, and H. V. Poor, Multiple access techniques for 5G
wireless networks and beyond. Springer, 2019.
[6] Y.-P. E. Wang, X. Lin, A. Adhikary, A. Grovlen, Y. Sui, Y. Blankenship,
J. Bergman, and H. S. Razaghi, “A primer on 3gpp narrowband internet
of things,” IEEE communications magazine, vol. 55, no. 3, pp. 117–123,
2017.
[7] C. Bockelmann, N. K. Pratas, G. Wunder, S. Saur, M. Navarro, D. Gre-
goratti, G. Vivier, E. De Carvalho, Y. Ji, Ä. StefanoviĢ
G, P. Popovski,
Q. Wang, M. Schellmann, E. Kosmatos, P. Demestichas, M. Raceala-
Motoc, P. Jung, S. Stanczak, and A. Dekorsy, “Towards massive connec-
tivity support for scalable mmtc communications in 5g networks,” IEEE
Access, vol. 6, pp. 28969–28992, 2018.
[8] A. Lavric and V. Popa, “Internet of things and loraâ ˇ
D´
c low-power wide-
area networks: A survey,” in 2017 International Symposium on Signals,
Circuits and Systems (ISSCS), pp. 1–5, 2017.
[9] K. Mekki, E. Bajic, F. Chaxel, and F. Meyer, “A comparative study of
lpwan technologies for large-scale iot deployment,” ICT Express, vol. 5,
no. 1, pp. 1 – 7, 2019.
[10] A. SEMTECH and M. Basics, “An1200. 22,” LoRa Modulation Basics,
vol. 46, 2015.
[11] A. Gupta and R. K. Jha, “A survey of 5g network: Architecture and
emerging technologies,” IEEE Access, vol. 3, pp. 1206–1232, 2015.
[12] K. Mikhaylov, J. Petajajarvi, and J. Janhunen, “On lorawan scalability:
Empirical evaluation of susceptibility to inter-network interference,” in
2017 European Conference on Networks and Communications (EuCNC),
pp. 1–6, June 2017.
[13] I. Butun, N. Pereira, and M. Gidlund, “Analysis of lorawan v1. 1 security,”
in Proceedings of the 4th ACM MobiHoc Workshop on Experiences with
the Design and Implementation of Smart Objects, p. 5, ACM, 2018.
[14] LoRa Alliance Technical Committee and others, LoRaWAN Back-End
Interfaces v1.0. LoRa Alliance, 5177 Brandin Court. Fremont, CA 94538,
1.0 ed., 10 2017.
[15] ETSI, “5g; security architecture and procedures for 5g system (3gpp ts
33.501 version 15.1.0 release 15),” tech. rep., jul 2018. DTS/TSGS-
0333501vf10.
[16] GSM Association, “5g roaming guidelines, version 1.0.”
[17] D. Fang, Y. Qian, and R. Q. Hu, “Security for 5g mobile wireless net-
works,” IEEE Access, vol. 6, pp. 4850–4874, 2018.
[18] T. S. G. Services and S. Aspects, “System architecture for the 5g system
(5gs) - 3gpp ts 23.501 version 16.3.0 release 16, stage 2,” tech. rep., dic
2019.
[19] B. Aboba, M. Beadles, J. Arkko, and P. Eronen, “The Network Access
Identifier.” RFC 4282, Dec. 2005.
[20] T. S. G. C. Network and Terminals, “Numbering, addressing and identifi-
cation - 3gpp ts 23.003 version 16.1.0,” tech. rep., dic 2019.
[21] R. Khan, P. Kumar, D. N. K. Jayakody, and M. Liyanage, “A survey
on security and privacy of 5g technologies: Potential solutions, recent
advancements and future directions,” IEEE Communications Surveys &
Tutorials, 2019.
[22] G. A. Akpakwu, B. J. Silva, G. P. Hancke, and A. M. Abu-Mahfouz,
“A Survey on 5G Networks for the Internet of Things: Communication
Technologies and Challenges,” IEEE Access, vol. 6, pp. 3619–3647, 2017.
[23] J. Navarro-Ortiz, S. Sendra, P. Ameigeiras, and J. M. Lopez-Soler, “Inte-
gration of lorawan and 4g/5g for the industrial internet of things,” IEEE
Communications Magazine, vol. 56, pp. 60–67, Feb 2018.
[24] R. Yasmin, J. PetÃd’jÃd’jÃd’rvi, K. Mikhaylov, and A. Pouttu, “On the
integration of lorawan with the 5g test network,” in 2017 IEEE 28th
Annual International Symposium on Personal, Indoor, and Mobile Radio
Communications (PIMRC), pp. 1–6, Oct 2017.
[25] A. Neumann, L. Wisniewski, T. Musiol, C. Mannweiler, B. Gajic, R. S.
Ganesan, and P. Rost, “Abstraction models for 5G mobile networks inte-
gration into industrial networks and their evaluation,” pp. 88–101, 2020.
[26] J. Arkko, V. Lehtovirta, and P. Eronen, “Improved Extensible Authen-
tication Protocol Method for 3rd Generation Authentication and Key
Agreement (EAP-AKA’).” RFC 5448, May 2009.
[27] D. Garcia-Carrillo, R. Marin-Lopez, A. Kandasamy, and A. Pelov, “A
coap-based network access authentication service for low-power wide area
networks: Lo-coap-eap,” Sensors, vol. 17, no. 11, 2017.
[28] E. Pearce and E. Lawson, “Lora alliance passes 100 lorawanâˇ
D´
c network
operator milestone with coverage in 100 countries,” 2019.
[29] J. Koon, LoRaWAN½
o Empowers Very Low-power, Wireless Applica-
tions: The Future of Low-power Wireless Network. "Lora Alliance", nov
2019.
[30] H. Khan, B. Dowling, and K. M. Martin, “Identity confidentiality in 5g
mobile telephony systems,” in Security Standardisation Research (C. Cre-
mers and A. Lehmann, eds.), (Cham), pp. 120–142, Springer International
Publishing, 2018.
[31] A. Lilly, “Imsi catchers: hacking mobile communications,” Network Secu-
rity, vol. 2017, no. 2, pp. 5 – 7, 2017.
[32] A. Shaik, R. Borgaonkar, N. Asokan, V. Niemi, and J.-P. Seifert, “Practical
attacks against privacy and availability in 4g/lte mobile communication
systems,” p. 16, 01 2016.
[33] M. G. Consourtium, “Mosaic5g web portal.” http://mosaic-5g.io, 2020.
Accessed: 2020-01-25.
[34] O. Brocaar, “Chirpstack, open-source lorawan½
o network server stack.”
https://www.chirpstack.io/, 2020. Accessed: 2020-01-25.
[35] J.-P. Lang, “Osmocom web portal.” http://osmocom.org/, 2019. Accessed:
2020-01-25.
[36] P. Maier, “Osmocom osmo-sim-auth library.
http://git.osmocom.org/osmo-sim-auth/, 2019. Accessed: 2020-01-
25.
[37] Osmocom Project, “Osmocom osmo-auc-gen library.
https://osmocom.org/projects/osmo-sim-auth, 2012. Accessed: 2020-01-
25.
[38] NEXTEPC INC., “Nextepc 5g project.” https://nextepc.org, 2010. Ac-
cessed: 2020-01-25.
[39] LoRa Alliance Technical Committee Regional Parameters Workgroup,
LoRaWAN 1.1 Regional Parameters. LoRa Alliance, Inc, 2400 Camino
Ramon, Suite 375. San Ramon, CA 94583, 1.1 ed., 1 2018.
ELENA M. TORROGLOSA GARCIA Elena
Torroglosa received the B.S., M.S., and Ph.D.
degrees in computer science from the Univer-
sity of Murcia, Murcia, Spain. She has been
involved in multiple research projects in di-
verse fields such as AAA/Identity management
(SWIFT, GEMBus, STORK2.0, GN4-1-SA5-T1,
GN4-2-JRA3T3, OLYMPUS), design of inter-
federation solutions (GN4-1-SA5-T1: STORK2
with eduGAIN, GN4-2-JRA3T3: eIDAS with
eduGAIN), ¢
aExperimentation Infrastructures such as OpenLAB. Cur-
rently, she is currently doing a 2-years stay at the School of Computing,
Engineering and Physics Science of the University of the West of Scotland
thanks to postdoctoral grant of the CARM (20938/PD/18), through the
Seneca Foundation-Agency for Science and Technology of the Region of
Murcia (Spain). Her current stay at UWS is focused on the development
of advanced identity management systems for IoT devices on 5G networks,
using innovative interoperability mechanisms as well as cognitive methods
to improve the management of infrastructure, users and services.
VOLUME 4, 2016 17
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2020.2998416, IEEE Access
Author et al.: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS
JOSE M. ALCARAZ-CALERO , Full Professor
in Networks at University of the West of Scotland,
United Kingdom. He is technical co-coordinator
of the EU-H2020 5G-PPP Phase I SELFNET and
EU-H2020 5G-PPP Phase II SliceNet projects.
Alcaraz-Calero has more than 200 publications in
a wide range of professional interests including
cognitive pipelines, network management, moni-
toring and control, automation and orchestration,
cyber security, data analytics and computer vision.
(jose.alcaraz-calero@uws.ac.uk).
JORGE BERNAL BERNABE received the B.S.,
M.S., and Ph.D. degrees in computer science as
well as the M.B.A. degree from the University
of Murcia, Murcia, Spain. He was granted with
the Best Ph.D. Thesis Award from the School of
Computer Science of the University of Murcia.
Currently, he is a Postdoctoral Researcher in the
Department of Information and Communications
Engineering of the University of Murcia. Jorge
Bernal has been Visiting Researcher in the Cloud
and Security Lab of Hewlett-Packard Laboratories, Bristol, UK, and author
of several book chapters and more than 40 papers in international top-level
conferences and journals. He has been involved in the scientific committee of
numerous conferences and served as a reviewer for multiple journals. During
the last years, he has been working in several European research projects FP7
and H2020, such as DESEREC, Semiramis, Inter-Trust, SocIoTal, ARIES,
OLYMPUS, Anastacia, CyberSec4EU or INSPIRE-5GPlus. His scientific
activity is mainly devoted to the security, trust, and privacy management in
distributed systems. He is also interested in security and privacy aspects in
the Internet of Things.
ANTONIO SKARMETA Antonio Skarmeta re-
ceived his Ph.D. degree in computer science from
the University of Murcia, Murcia, Spain, M.S.
degree in computer science from the University of
Granada, Granada, Spain, and B.S. degree (with
honors). Since 2009, he has been Professor at
University of Murcia, Murcia, Spain. Skarmeta
has worked on different research projects in the
national and international area in the networking,
security, and IoT area, like Euro6IX, ENABLE,
DAIDALOS, SWIFT, SEMIRAMIS, SMARTIE, SOCIOTAL, and IoT6. His
main interest is in the integration of security services, identity, IoT, and
smart cities. He has been the Head of the research group ANTS since its
creation in 1995. He is also an Advisor to the Vice Rector of Research of the
University of Murcia for international projects and Head of the International
Research Project Office. Since 2014, he has been the Spanish National
Representative for the MSCA within H2020. He has published over 200
international papers and has been a member of several program committees.
He has also participated in standardization for IETF, ISO, and ETSI.
18 VOLUME 4, 2016
... The use of mm-Wave in 5G wireless systems is motivated by the limited availability of sub-6 GHz spectrum. This is because mm-Wave has a significant amount of unprocessed bandwidth available and can support multi-gigabitper-second communications for cellular [4]- [6], backhaul [7], office [8], and in-home applications [9], [10]. ...
Article
Full-text available
Accurate link budget calculations and efficient 5G wireless application system design depend on the path loss modelling. Research on 5G mm-wave propagation in indoor environments shows capacity variations due to different models. Future models need validation, simulation, and improvement for better network quality. This paper introduces a novel method for estimating the path loss value in indoor scenarios. It uses a combination of electromagnetic calculation and machine learning. Using electromagnetic software, we design the indoor environment and calculate path loss between the receiver and the transmitter antennas, which are situated randomly with respect to the transmitters for better coverage. The transmitter antenna is modeled by employing the 3GPP standards. The indoor NLOS and LOS scenarios are measured over a 47-m separation distance between the RX and TX antenna locations. As it comes to fitting real measured data that has been acquired via measurement campaigns, the suggested models perform better overall. The achieved data is used to predict path loss using empirical models like FI and CI, and the mean absolute error percentages obtained are 5.87 and 6.61, respectively. After that, deep neural network and CatBoosting methods are employed to predict and estimate the PL precisely in the indoor environment. The mean absolute error percentages obtained are 4.4 and 3.3 for deep neural network and CatBoosting, respectively. Predicting PL, deep neural network, and CatBoosting methods outperform CI and FI by modelling complex, non-linear relationships, incorporating a broader range of features, adapting to diverse environments, and generalizing more effectively from data. These benefits are well-matched for modern wireless communication systems, where accurate estimation of signal loss is essential for maximizing network performance.
... Some studies analyzed in this extensive survey propose or verify strategies to prevent general threats such as eavesdropping [3,29,30,36,106], DoS [25,57,181], EDoS [195], scanning attacks [33], IMSI catchers [134,191], spooing attacks [39,45,100,100,201], resource depletion attacks (e.g., botnet attacks [66,147]), jamming [20,69,80], localization attack [152], pilot contamination [200,202], pollution attacks [9,10,193], false data injection [127], DDoS [54,71,98,118,155,180], and DRDoS [38,76]. Other proposed solutions address secure handover (e.g., for heterogeneous IoT networks [188]), enabling devices to join domains with trust (e.g., using authentication frameworks [42,43,132] and protocols [164]). Some studies concern the proposal of improved authentication/authorization [6,15,122,140,177], architectures [31,60,72,120,170,196], lightweight security [8,125,158,166,210], security schemes (models or protocols) [17,19,35,48,91], security platforms (or systems) [44,53,139,146,151], algorithms (or methods) [37,112,142,176,182], SDN/NFV-based core NS [116], anomaly/threat detection [16,85,131,145,207], controlling NS access/use [121], ensuring NS isolation [67], ensuring intra-slice security [32], ensuring security in D2D communications [1,2,156,159,199,216], security based on blockchain [59,115,169,179,194], and testbeds for 5G experimentation [49,63,94,143,168]. ...
Article
Ensuring the security of vertical applications in fifth-generation (5G) mobile communication systems and previous generations is crucial. These systems must prioritize maintaining the confidentiality, integrity, and availability of services and data. Examples of vertical applications include smart cities, smart transportation, public services, Industry 4.0, smart grids, smart health, and smart agriculture. Each vertical application has specific security requirements and faces unique threats within the mobile network environment. Thus, it is essential to implement comprehensive and robust security measures. This approach helps minimize the attack surface and effectively manage risks. This survey thoroughly examines mobile networks and their security challenges in vertical applications, shedding light on associated threats and potential solutions. Our study considers the interplay between security considerations in 5G, legacy networks, and vertical applications. We emphasize the challenges, opportunities, and promising directions for future research in this field and the importance of securing vertical applications in the evolving landscape of mobile technology.
... This approach could be promising, in the current project, however, no adaptation of the public network can be implemented. Torroglosa-Garci et al. propose two approaches to establish handover roaming between different wireless networks like LoRaWAN and 5G [7]. However, this requires adaptations to the 5G and LoRaWAN standard and is therefore, also not feasible for an existing network. ...
Book
yang semakin terintegrasi untuk menciptakan pengalaman pengguna yang lebih kaya dan interaktif. IoT merujuk pada jaringan perangkat yang terhubung melalui internet, memungkinkan mereka untuk berkomunikasi dan berbagi data secara real-time. Perangkat ini mencakup segala sesuatu mulai dari sensor sederhana hingga perangkat rumah pintar dan kendaraan otonom. Ketika IoT digabungkan dengan multimedia, yang mencakup konten seperti audio, video, gambar, dan teks, hasilnya adalah ekosistem yang sangat cerdas di mana informasi multimedia dapat dikumpulkan, dianalisis, dan disajikan secara dinamis berdasarkan data yang diperoleh dari perangkat IoT Buku ini membahas : Bab 1 Pengantar Internet of Things (IoT) Bab 2 Arsitektur dan Protokol IoT Bab 3 Pengantar Multimedia dalam IoT Bab 4 Sensor dan Perangkat dalam IoT Bab 5 Pengolahan dan Penyimpanan Data Multimedia Bab 6 Transmisi Data Multimedia dalam IoT Bab 7 Aplikasi IoT Multimedia dalam Smart Home Bab 8 Aplikasi IoT Multimedia dalam Kesehatan dan Kebugaran Bab 9 Aplikasi IoT Multimedia dalam Retail dan Pemasaran Bab 10 Aplikasi IoT Multimedia dalam Pendidikan Bab 11 Keamanan dan Privasi dalam IoT Multimedia
Article
Full-text available
Security has become the primary concern in many telecommunications industries today as risks can have high consequences. Especially, as the core and enable technologies will be associated with 5G network, the confidential information will move at all layers in future wireless systems. Several incidents revealed that the hazard encountered by an infected wireless network, not only affects the security and privacy concerns, but also impedes the complex dynamics of the communications ecosystem. Consequently, the complexity and strength of security attacks have increased in the recent past making the detection or prevention of sabotage a global challenge. From the security and privacy perspectives, this paper presents a comprehensive detail on the core and enabling technologies, which are used to build the 5G security model; network softwarization security, PHY (Physical) layer security and 5G privacy concerns, among others. Additionally, the paper includes discussion on security monitoring and management of 5G networks. This paper also evaluates the related security measures and standards of core 5G technologies by resorting to different standardization bodies and provide a brief overview of 5G standardization security forces. Furthermore, the key projects of international significance, in line with the security concerns of 5G and beyond are also presented. Finally, a future directions and open challenges section has included to encourage future research.
Book
Full-text available
This book presents comprehensive coverage of current and emerging multiple access, random access, and waveform design techniques for 5G wireless networks and beyond. A definitive reference for researchers in these fields, the book describes recent research from academia, industry, and standardization bodies. The book is an all-encompassing treatment of these areas addressing orthogonal multiple access and waveform design, non-orthogonal multiple access (NOMA) via power, code, and other domains, and orthogonal, non-orthogonal, and grant-free random access. The book builds its foundations on state of the art research papers, measurements, and experimental results from a variety of sources. Notably, it Includes orthogonal and non-orthogonal waveforms for 5G new radio and beyond: CP-OFDM, UF-OFDM, f-OFDM, WOLA, FBMC, and GFDM; Features NOMA via the power domain (fundamentals, clustering, power allocation, experimental trials, etc.) and the code and other domains (SCMA, IDMA, LDS-CDMA, PDMA, IGMA, RSMA, and RDMA); Outlines random access techniques (CSMA, CSMA/CD, ALOHA, slotted ALOHA, and LoRa), applications and use cases of 5G networks (eMBB, URLLC, mMTC, IoT, and V2V), as well as challenges and future directions in multiple access, random access, and waveform design.
Conference Paper
Full-text available
LoRa and the LoRaWAN specification is a technology for Low Power Wide Area Networks (LPWAN) designed to allow connectivity for connected objects, such as remote sensors. Several previous works revealed various weaknesses regarding the security of LoRaWAN v1.0 (the official 1st draft) and these led to improvements included in LoRaWAN v1.1, released on Oct 11, 2017. In this work, we provide the first look into the security of LoRaWAN v1.1. We present an overview of the protocol and, importantly, present several threats to this new version of the protocol. Besides, we propose our own ramification strategies for the mentioned threats, to be used in developing next version of LoRaWAN. The threats presented were not previously discussed, they are possible even within the security assumptions of the specification and are relevant for practitioners implementing LoRa-based applications as well researchers and the future evolution of the LoRaWAN specification.
Article
Full-text available
The fifth generation of cellular communication systems is foreseen to enable a multitude of new applications and use cases with very different requirements. A new 5G multiservice air interface needs to enhance broadband performance as well as provide new levels of reliability, latency and supported number of users. In this paper we focus on the massive Machine Type Communications (mMTC) service within a multi-service air interface. Specifically, we present an overview of different physical and medium access techniques to address the problem of a massive number of access attempts in mMTC and discuss the protocol performance of these solutions in a common evaluation framework.
Article
Full-text available
By 2020, more than 50 billion devices will be connected through radio communications. In conjunction with the rapid growth of the Internet of Things (IoT) market, low power wide area networks (LPWAN) have become a popular low-rate long-range radio communication technology. Sigfox, LoRa, and NB-IoT are the three leading LPWAN technologies that compete for large-scale IoT deployment. This paper provides a comprehensive and comparative study of these technologies, which serve as efficient solutions to connect smart, autonomous, and heterogeneous devices. We show that Sigfox and LoRa are advantageous in terms of battery lifetime, capacity, and cost. Meanwhile, NB-IoT offers benefits in terms of latency and quality of service. In addition, we analyze the IoT success factors of these LPWAN technologies, and we consider application scenarios and explain which technology is the best fit for each of these scenarios.
Article
Full-text available
The advanced features of 5G mobile wireless network systems yield new security requirements and challenges. This paper presents a comprehensive survey on security of 5G wireless network systems compared to the traditional cellular networks. The paper starts with a review on 5G wireless networks particularities as well as on the new requirements and motivations of 5G wireless security. The potential attacks and security services with the consideration of new service requirements and new use cases in 5G wireless networks are then summarized. The recent development and the existing schemes for the 5G wireless security are presented based on the corresponding security services including authentication, availability, data confidentiality, key management and privacy. The paper further discusses the new security features involving different technologies applied to 5G such as heterogeneous networks, device-to-device communications, massive multiple-input multiple-output, software defined networks and Internet of Things. Motivated by these security research and development activities, we propose a new 5G wireless security architecture, based on which the analysis of identity management and flexible authentication is provided. As a case study, we explore a handover procedure as well as a signaling load scheme to show the advantage of the proposed security architecture. The challenges and future directions of 5G wireless security are finally summarized.
Conference Paper
The fifth generation of mobile networks (5G) will provide capabilities for its utilization in the communication in production systems. For several technical and commercial reasons, complementing industrial wired and wireless communication technology by 5G is more likely than replacing them completely [WSJ17]. This paper sketches abstraction models of 5G networks for their integration into industrial networks. Dependabilities from the type of the industrial network, constraints of the models and the impact of the resulting architecture to data plane and control plane of the overall hybrid network will be discussed. In addition, metrics for the evaluation of the modeling approaches from an end-to-end user application perspective will be figured out.
Article
Current forecasts predict that the Industrial Internet of Things will account for about 10 billion devices by 2020. Simultaneously, unlicensed low-power wide area networks are gaining momentum due to their low cost, low power, and long range characteristics, which are suitable for many IIoT applications, in addition to the usage of unlicensed bands. In this article, a solution is proposed to seamlessly integrate LoRaWAN, an open and standardized LPWAN technology, with 4G/5G mobile networks, thus allowing mobile network operators to reutilize their current infrastructures. This proposal is transparent to LoRaWAN end devices and to the EPC, since only the LoRaWAN gateway needs to be modified. The gateway acts as an evolved Node B from the core network perspective, implementing part of the eNB protocol stack. All data packets transported over the core network are both encrypted and integrity protected, hence achieving end-toend security. As a proof of concept, this solution has been implemented and validated with an open source EPC.