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Electric vehicles (EVs) have been slowly replacing conventional fuel based vehicles since the last decade. EVs are not only environment-friendly but when used in conjunction with a smart grid, also open up new possibilities and a Vehicle-Smart Grid ecosystem, commonly called V2G can be achieved. This would not only encourage people to switch to environment-friendly EVs or Plug-in Hybrid Electric Vehicles (PHEVs), but also positively aid in load management on the power grid, and present new economic benefits to all the entities involved in such an ecosystem. Nonetheless, privacy and security remains a serious concern of smart grids. The devices used in V2G are tiny, inexpensive, and resource constrained, which renders them susceptible to multiple attacks. Any protocol designed for V2G systems must be secure, lightweight, and must protect the privacy of the vehicle owner. Since EVs and charging stations are generally not guarded by people, physical security is also a must. To tackle these issues, we propose Physical Unclonable Functions (PUF) based Secure User Key-Exchange Authentication (SUKA) protocol for V2G systems. The proposed protocol uses PUFs to achieve a two-step mutual authentication between an EV and the Grid Server. It is lightweight, secure, and privacy preserving. Simulations show that the proposed protocol performs better and provides more security features than state-of-the-art V2G authentication protocols. The security of the proposed protocol is shown using a formal security model and analysis.
Lightweight Mutual Authentication Protocol for
V2G Using Physical Unclonable Function
Gaurang Bansal, Member, IEEE, Naren, Vinay Chamola, Member, IEEE, Biplab Sikdar, Senior Member, IEEE,
Neeraj Kumar, Senior Member, IEEE and Mohsen Guizani, Fellow, IEEE
Abstract—Electric vehicles (EVs) have been slowly replacing
conventional fuel based vehicles since the last decade. EVs are
not only environment-friendly but when used in conjunction
with a smart grid, also open up new possibilities and a Vehicle-
Smart Grid ecosystem, commonly called V2G can be achieved.
This would not only encourage people to switch to environment-
friendly EVs or Plug-in Hybrid Electric Vehicles (PHEVs), but
also positively aid in load management on the power grid, and
present new economic benefits to all the entities involved in
such an ecosystem. Nonetheless, privacy and security remains
a serious concern of smart grids. The devices used in V2G
are tiny, inexpensive, and resource constrained, which renders
them susceptible to multiple attacks. Any protocol designed for
V2G systems must be secure, lightweight, and must protect the
privacy of the vehicle owner. Since EVs and charging stations are
generally not guarded by people, physical security is also a must.
To tackle these issues, we propose Physical Unclonable Functions
(PUF) based Secure User Key-Exchange Authentication (SUKA)
protocol for V2G systems. The proposed protocol uses PUFs to
achieve a two-step mutual authentication between an EV and the
Grid Server. It is lightweight, secure, and privacy preserving.
Simulations show that the proposed protocol performs better
and provides more security features than state-of-the-art V2G
authentication protocols. The security of the proposed protocol
is shown using a formal security model and analysis.
Index Terms—authentication, security, smart grid, V2G, PUF
Electric Vehicles’ batteries enable the functionality of V2G
networks. The purpose of V2G is to manage the energy trading
for battery-poweblack electric vehicles as well as the power
grid. This is necessary in order to use the grid’s energy more
efficiently [1]. The electrical energy stored in the EV batteries
can serve as a source for the power grid and other energy
deficient EVs. When the load on the grid is high, the energy
stored in the EVs’ batteries could be used to pump power into
the grid. On the other hand, when the load on the grid is low,
the excess power in the grid could be used to charge the EV
batteries and avoid wastage [2]. V2G networks could also be
used for power regulation [3] or for storing power generated by
Gaurang Bansal, Naren and Vinay Chamola are with the Department of
Electrical and Electronics Engineering, BITS-Pilani, Pilani Campus, India
333031 (e-mail:, f2015547@pilani.bits-,
Biplab Sikdar is with the Department of Electrical and Computer Engi-
neering, National University of Singapore, Singapore 119077 (e-mail: bsik-
Neeraj Kumar is with the Department of Computer Science, Thapar
University, Patiala, India 147004 (e-mail:
Mohsen Guizani is with the Department of Computer Science, Qatar
University, Doha 2713, Qatar (e-mail: ).
Digital Object Identifier: XXXXXXXXXXXX
Fig. 1: System model
renewable sources such as wind power [4]. Thus, nowadays,
V2G for smart grids presents great practical applications.
The global demand for electrical power is predicted to climb
82% by the year 2030. Therefore, Power grids are aiming
to reduce the number of additional generators required. They
employ demand-response techniques [5] to reduce power con-
sumption and increase efficiency. Although such techniques
offer many benefits, security and privacy issues remain to be
significant downsides [6, 7]. A lot of information is communi-
cated during energy exchange between a vehicle and a service
provider. However, an adversary could compromise this flow
of information, either by tampering with it or capturing it
entirely [8]. This could lead to unfair or imbalanced energy
transactions between the two parties. Moreover, the victim’s
information (that could be captured) may be used in criminal
activities and targeted advertisements. The devices used in
V2G are inexpensive, small, and simple [9]. The EVs are
usually parked in locations which are easy to access. This
means that an adversary could easily capture the V2G devices
on these vehicles. Therefore, it is important to make V2G
entities/devices secure against physical attacks. For instance,
an adversary could access security keys stored in the device
memory and initiate various attacks. Physical Unclonable
Functions (PUFs) have emerged as a promising solution for
protection against physical attacks. PUFs eliminate the need
to store secret keys in the devices’ memory and rely on the
exchange of challenge-response pairs. The challenge-response
mechanism of PUFs exploits the inherent fabrication or man-
ufacturing process variabilities involved in making integrated
circuits (ICs) [10]. The response or output of a PUF depends
on both the input as well as the physical microstructure of
the device [11]. The physical randomness induced through the
fabrication process variations makes each PUF device unique,
i.e., two identical copies can never be made.
In V2G systems, an aggregator is a charging station which
acts as a mediator between the EVs and the power grid. Se-
cure communications in such scenarios require authentication
between the EVs and the aggregator, between aggregator and
the grid, and between EVs and the grid as well. The proposed
Secure User Key-Exchange Authentication (SUKA) protocol
achieves the authentications mentioned above using a two-
stage process. Using pseudonym IDs (PID), the identity of
the vehicle is masked to protect the vehicle owner’s identity
and location. Two different session keys are established in
SUKA, one between the aggregator and the grid, and another
between any EV and the aggregator. These session keys are a
function of the PUFs installed on the aggregator and the EV,
respectively. This ensures the secrecy of the communication
and eliminates the need to store any secret keys in the memo-
ries of the EVs and the aggregator. The proposed protocol uses
simple cryptographic operations, which makes it lightweight
and energy efficient. The number of message exchanges is also
limited, which results in a lower communication overhead. The
major contributions of this paper are highlighted below:
We propose a security scheme, SUKA, for V2G appli-
cations where both the mobile EVs and the stationary
aggregators are provisioned with PUFs for secure com-
SUKA puts the safety of the EV and its owner as top
priority by first achieving authenication of the aggregator
with the power grid server. Only if this is achieved,
the aggregator will be able to accommodate the EV.
Our scheme ensures security even in the case of a
compromised aggregator.
SUKA ensures mutual authentication, identity protection,
message integrity and is tolerant to man-in-the-middle
(MITM) attacks, impersonation attacks, replay attacks
and node tampering attacks without having to store any
secret keys in the EVs or the stationary aggregators. The
records of EVs cannot be tracked even if the EVs and/or
the stationary aggregators are compromised.
SUKA establishes different session keys between the EV
and the aggregator, and between aggregator and the power
grid server. These session keys change randomly in each
round of authentication and cannot be accessed by an
adversary even if it gains physical access to both the EV
and the aggregator.
The rest of this paper is organized as follows. Section II
discusses the related work in V2G systems. Section III presents
a brief introduction to PUFs, the network model, security
goals, assumptions for the V2G system, and the notations used
in our paper. Section IV presents our MA protocol (SUKA).
Section V presents a formal security analysis of the proposed
protocol. We analyze the performance of our protocol and
compare it with state-of-the protocols in Section VI and finally
conclude the paper in Section VII.
Kempton and Tomi´
c [12] first conceived the idea of V2G
in 2004. Before the protocols for V2G networks could be
developed, the structure of a V2G network had to be well
defined, and the impact of V2G on the power grid had to be
analyzed. This work was carried out by the authors in [13,
14, 15, 16, 17]. Privacy, secure communication, and efficiency
are among the most important aspects of a V2G protocol
[18]. Privacy preservation in V2G environments has received
considerable attention in the existing literature [19, 20, 21, 22].
Yang et al. have presented a protocol P2in [19] which
achieves privacy for individual electric vehicles (EVs) and the
rewarding scheme which is crucial for proper implementation
of V2G. Liu et al. present their scheme, AP 3A, which is
capable of identifying whether an EV is in its home or visiting
network [20]. AP 3Acommunicates the aggregated power
status of the vehicles connected to an aggregator instead of
revealing individual power status, thus achieving privacy for
each EV. Liu et al. have presented a scheme which identifies
the different roles played by an individual EV, i.e., customer,
storage or generator [22]. In each role, their scheme ROP S
addresses different privacy concerns. Tsai and Lo achieve
mutual authentication and identity protection with the use
of one private key which is given by a third-party anchor.
This enables the smart-meters to quickly authenticate with the
service provider. Abdallah and Shen propose a computation-
ally less intensive privacy-preserving scheme in [24]. They
identify that the authentication of EVs in the V2G system is
specifically problematic. Therefore, the power grid takes the
responsibility of ensuring the confidentiality and integrity of
the communication. By reducing the number of exchanged
messages, they achieve less overhead. Odelu et al. present
a secure authenticated key agreement scheme [25] under the
Canett-Krawczyk adversary (CK-adversary) model for smart
grids. Shen et al. propose a privacy-preserving key agreement
protocol for V2G networks in [26]. Their protocol ensures
security by the use of a session key and ensures privacy using
a self-synchronization mechanism.
Protocols for authentication in V2G environments have been
proposed in [27, 28, 29]. Saxena and Choi have presented an
authentication scheme for large V2G networks where vehicles
move from their home network to other networks as visitors
[30]. They propose a mutual authentication scheme which pro-
tects against impersonation, key-based and data-based attacks.
Tao et al. have presented capacity-aware protocol AccessAuth
in [31] which takes into consideration the capacity limitations
of each V2G network domain, of the EVs, and the mobility of
the EVs for admission control. Based on prior information of
trust between V2G network domains, they present a high-level
authentication model and procedure to ensure that only autho-
rized entities conduct the sessions. Gope and Sikdar have used
one-way noncollision hash functions to propose a lightweight
mutual authentication protocol [32]. Fouda et al. have pro-
posed a lightweight message authentication scheme in [33].
In their scheme, smart meters at different levels in the smart-
grid achieve mutual authentication among themselves, and a
shared session key is established. They achieve lightweight
message authentication using this shared session key along
with a hash-based authentication code mechanism. Although
this scheme was presented for smart grid communications, it
can very well be extended to V2G networks.
While many privacy-preserving, lightweight mutual au-
thentication, and key establishment protocols exist for V2G
systems, none of them provide all the required security and
privacy features along with protection against all types of
attacks, especially protection against physical attacks. If a
protocol does provide perfect security, then it either requires
resource-heavy hardware or is computationally complex.
Table I lists the notations used in this paper and their
TABLE I: Notations
Notation Description
V, IDVVehicle and its ID
M, IDMAggregator(mediator) and its ID
GGrid Server
kConcatenation operator
XOR operation
FA public non-linear function
Message Msg is encrypted
using key k
Message Msg is sent from
V2G entity Pto Q
MAC(X)Message authentication code
(MAC) of X
Nonces generated
at different stages
(C, K),(C0, K0)
(C00, K 00),(C#, K#)Challenge-response pairs of PUF
A PUF is based on a unique physical property of a device
which is unique as the biometrics of a human. The distin-
guishing attribute of a PUF is that it relies on a physical basis,
making it impossible to reproduce a PUF using cryptographic
primitives. Additionally, the term “physical unclonable” in-
dicates that it is computationally infeasible or difficult to
produce a physically identical PUF [34]. By using PUFs in
an interconnected system such as IoT or V2G systems, every
single device can have its own unique “fingerprint” which
cannot be cloned or reproduced [35]. A PUF behaves like
a mathematical function whose input (challenge) and output
(response) are both in the form of a string of bits. A PUF
function can be represented as:
K=P U F (C)(1)
where the challenge Cis given as input and response, Kis
the corresponding output to that challenge.
PUFs are designed deliberately so that the response to a par-
ticular challenge depends on the individual physical disorder
present in the PUF. Therefore, each PUF response is not only
a function of the challenge applied, but also a function of its
physical disorder. While it is clear that different challenges to
the same PUF will give different responses, PUFs also show
the following unique characteristics with respect to their input
Cand output K:
1) If an input Cis given to the same PUF many times,
it produces the same response Kwith a very high
2) If the same input Cis given to different PUFs, the
responses obtained from each PUF differ greatly from
each other with a very high likelihood.
The characteristics mentioned above apply to non-ideal PUFs.
Due to environmental and circuit noises, a non-ideal PUF
cannot guarantee the exact same response Kfor an input C,
hence the word ‘high likelihood’ was used above. There will
always be some bit-errors depending on the type of PUF used.
Although error correcting techniques such as fuzzy extractors
could be used in order to combat this problem, that would
result in unnecessary overhead for the MA process. Therefore,
the PUFs employed in the proposed protocol have to be ideal
in nature, i.e., without any bit errors. This would ensure 100%
availability of the V2G system.
In the past few years, several types of ideal PUFs have
been developed, which ensure 0% Bit-Error-Rate (BER) over
a wide range of temperature and voltage fluctuations. The
authors of [36] have been able to achieve 0% BER in SRAM
PUFs, the authors of [37] achieved 0% Bit-Error-Rate (BER)
design with their VIA-PUF. Several other works [38, 39, 40]
have also been able to achieve 0% Bit-Error-Rate (BER).
These ICs are very small, measuring just a few millimeters in
dimensions and require just a few Volts (1-5 V) to operate,
which makes them ideal for the V2G scenario. By using
Ideal PUFs with on-board computers in V2G systems, stable
key generation can be achieved without the need for any
dedicated error correction hardware or software components
and thus promise lightweight and high-security performance
when used in V2G systems. However, ideal PUFs have been
developed very recently and have only been fabricated for
research purposes. Techniques to incorporate these PUFs on
the on-board computers of V2G systems, or System-on-Chip
designs (SoCs) with built-in PUFs do not exist at present.
Research and development of such ideal-PUF based solutions
for V2G systems to properly implant PUFs in the on-board
computers of EVs or aggregators can be considered as future
work, but further discussion on this topic is beyond the scope
of this paper.
A. Network Model
Figure 1 depicts the system model. This model consists of
three entities: EVs, aggregators (or mediators), and the grid.
An aggregator is a charging/discharging station where many
vehicles can come to charge/discharge their batteries. It acts as
a mediator between the EVs and the grid. EVs and aggregators
have limited resources, while the grid has significantly larger
resources. Aggregators and EVs have similar capabilities, but
aggregators have slightly larger memory and computation
power. As can be seen in Figure 1, multiple vehicles are
connected to an aggregator, and multiple aggregators connect
to the power grid. Our objective is to develop a mutual
authentication (MA) protocol between EVs and the grid. The
device on every vehicle and aggregator is equipped with a PUF.
Since a vehicle does not communicate directly with the grid,
to achieve MA between these two non-communicating parties,
all the intermediary nodes must be authenticated. Thus, MA
between the grid and a vehicle can be divided as MA between
the aggregator and the grid along with MA between the vehicle
and the aggregator. We assume here that there is no shared
key between a vehicle and its corresponding aggregator or
between an aggregator and the grid. Whenever a new vehicle
wants to register on the network, its challenge-response pair is
stored in the grid server. The grid is the only trusted authority,
and therefore, challenge-response pairs for all vehicles are
stored only in the grid. Nothing else is assumed in further
The server on the power grid starts with a set of initial
challenge-response pairs, (C, K)for each aggregator and
(C00, K 00)for each EV. The aggregator acquires this initial
set (C00, K 00)for the EV once the aggregator itself mutually
authenticated with the grid server. To set up a new aggregator
in a location or to deploy a new vehicle or on the roads,
initialization involves the initial set (C00, K 00)/(C, K)to be
sent to the power grid server using a secure channel. This
initialization can be done using a time-based one-time pass-
word algorithm (TOTP) [41] and an operator using a password.
After this exchange, the aggregator or vehicle can function
on its own without needing any operator or secure channel.
The grid server stores the actual identity IDM/I DV, and their
corresponding challenge response pairs, (C, K)and (C, K”),
for each aggregator and vehicle, while the aggregators or
vehicles themselves do not store anything. At the end of the
protocol, the ID of the EV, IDV, is replaced with pseudo-
identities for further exchanges.
We assume that an adversary can get hold of any commu-
nication that is happening between the EV and the aggregator
or the aggregator and the grid. An adversary has the power
to change, manipulate, and hide the data. It can inject new
packets, store the old messages, initiate a session, or pretend
to be a valid device. The objective of an attacker or adversary
is to gain access to the grid without being noticed. Adversaries
may be EV owners who want to exploit the V2G system in
order to cheat the service provider to charge their vehicles
for free or to get more money from the service provider when
they supply power to the grid from their EV. They may also be
rogue or unauthorized aggregators set up to cheat EV owners
by charging very high prices or not paying the EV owner
for the power they acquire. Such aggregators may also be
selling personal information of the EV owner to third-party
entities for the purpose advertisements. Adversaries may also
be criminals who may want to track the location/behaviour of
an EV owner by recording the aggregators visited by the EV
or criminals who may want to authenticate with the aggregator
with some other EV’s identity in order to escape the payment.
If an unauthorized or potentially dangerous entity manages
to authenticate with the grid server, it may disrupt energy
transactions and cause economic damage. Therefore, this paper
proposes a MA protocol that is resistant to various attacks such
as replay attacks, man-in-the-middle attacks, impersonation
attacks, etc.
B. Security Goals
1) Confidentiality: The energy transaction data must not
be visible to any unauthorized entity. For this, commu-
nication must be secret throughout, i.e., end-to-end. If
an unauthorized entity from either within the system
such as vehicles authenticated with other aggregators
or the currently connected aggregator gains access to
the messages which contain energy transaction details,
it must be impossible to make sense of it.
2) Message Integrity: It must be possible for the smart
grid server to verify if the message it receives from
the aggregator has been tampered with or compromised.
Since EVs and the grid server do not communicate
directly, the aggregator must also be able to do the same
for the messages received from the EVs.
3) Identity privacy: It must be impossible for an unautho-
rized entity to get hold of any personal information of the
vehicle owner of an EV. Even if an unauthorized entity
eavesdrops on the data exchanged within the V2G system,
it must not be able to figure out that the data is from a
particular vehicle or that two transactions are from the
same vehicle.
4) Authentication: Before any energy transaction can be
made, the aggregator must be authenticated with the grid
server. The aggregator must also be authenticated with
the vehicle, thus preventing any false energy exchanges.
C. Assumptions
The assumptions made in this paper are as follows:
PUF is a small hardware component that is present with
each participating device and is unique.
The communication between a device and its PUF is
secure and tamper-proof.
The grid is considered as a trusted authority and has
sufficient resources. On the other hand, EVs have limited
resources in terms of memory and computation power.
This section presents the proposed mutual authentication
protocol between the vehicle and the grid. Mutual authentica-
tion between the vehicle and the grid can be divided as mutual
authentication between:
Aggregator and grid.
Vehicle and aggregator.
A. Mutual Authentication Between Aggregator and Grid
1) When a vehicle wants to make a transaction, the aggre-
gator must authenticate the vehicle. The vehicle sends its
ID (IDV) along with a randomly generated nonce (NV)
to the aggregator with MsgV2M={IDV, NV}.
EV Aggregator
Evaluate K = PUF(C)
Fig. 2: Mutual authentication between aggregator and the power grid server.
2) The aggregator generates another random number, i.e.,
nonce (NI), and sends it along with its ID (IDM) to the
grid server with MsgM2G={IDM, NI}.
3) The first stage of our protocol begins with the aggre-
gator authenticating with the power grid server. This is
shown in Figure 2. The grid server receives a message
(MsgM2G={IDM, NI}) from the aggregator. It checks
if IDMexists in its memory and whether NIis fresh. If
either of the conditions fails, the authentication request
initiated by aggregator is terminated. Using IDM, it finds
the corresponding challenge-response pair (C, K)(Kcan
be split into m+ 1 sub-strings) in its memory:
K= (K0, K1, K2,· · · , Km)
It also generates a nonce (NB). To encrypt the message,
the server uses a block-based encryption mechanism with
mrounds. Let Fbe any non-linear function which is
public to everyone. Thus, even an adversary can know
what Fis. It can be verified that the security of the
protocol does not depend on F. The grid server then
computes the following:
M1=NIF(K0, NB)
M2=NBF(K1, M1)
Mi=Mi2F(Ki1, Mi1),3i<m
Mm=Mm1F(Km1, Mm1)
M= (Mm1||Mm)Km
4) The grid server sends C,M,Nalong with a MAC
(message authentication code) to the aggregator IDM,
as shown just after the first block under grid server in
EV Aggregator
Mutual Authentication Established
Session Key (Sk)
Fig. 3: Mutual authentication between electric vehicle and the aggregator.
Figure 2. The MAC is used to verify a few security
essentials. The first parameter in the MAC is to identify
the correct aggregator. Data integrity is ensured by the
second and third parameters. The freshness of the source
(grid server in this case) is identified by NB, which is
the last parameter. We use the same approach in the later
stages of the protocol as well.
5) On receiving the message from the grid server, aggregator
IDMgenerates the key Kas given in (1) using received
challenge Cas the input to its PUF. Then, the aggregator
calculates m, as shown below:
6) Using mand K, it then finds NBas shown in the
following equations by applying the same transformations
used in encryption operations of step 3.
Mi2=MiF(Ki1, Mi1),3i<m
NB=M2F(K1, M1)
NI=M1F(K0, NB).
The aggregator uses the MAC to verify the source of the
message, checks if its integrity has been compromised,
and determines whether the message is fresh or not.
If it fails to verify these security traits, authentication
is terminated by the aggregator. Else, a nonce NCis
generated. For future authentication, it generates a new
random challenge-response pair (C0, K0)using its PUF
and split K0into m+ 1 sub-strings:
K0= (K0
0, K0
1, K0
2,· · · , K0
It then calculates M0
i,M00,N0and session key Skas
M00 =M0
Sk=F(K0, NB)F(K0, NC).
7) Then, the aggregator sends C0,M00,N,N0, as well as the
MAC to the grid server. Next, it erases interim variables
from its memory. This time the MAC includes a fifth
parameter which is the session key, Sk. This ensures that
both aggregator and grid server have the same session
8) On receiving the message from the aggregator, the grid
server calculates NCusing N0and K0, obtains K0using
Mand K, and stores (C0, K0)in its memory. Then,
it calculates the session key, Skand verifies the MAC.
With the session key now established, MA between an
aggregator and the grid server is complete.
Sk=F(K0, NB)F(K0, NC)
B. Mutual Authentication between Vehicle and Aggregator
Mutual Authentication between Vehicle and Aggregator of
the proposed protocol is quite similar to Mutual Authentication
between Aggregator and Grid. Therefore, we only discuss the
key differences here, while the entire protocol is presented in
Fig. 3. The protocol for aggregator and grid server establishing
a session key Skbetween themselves, is shown as a small
box in Figure 3. The key difference of this stage is that, in
the first block under the EV, as shown in Figure 3, the EV
then calculates its new pseudonym or pseudo-ID, P IDV, to
be used the next time it wants to authenticate. This ensures
identity protection because an adversary will not be able to
figure out whether a previous transaction belonged to the same
EV or not. The pseudo-ID of the EV is also sent to the grid
server in message MsgM2G.
MsgM2G=E([E([C#, K#, P I DV], Sk2), Sk2], Sk)
The grid server decrypts message MsgM2Gwith Skto ob-
tain E([C#, K#, P I DV], Sk2)and Sk2. Next, it decrypts
E([C#, K#, P I DV], Sk2)with Sk2to obtain and store in
its memory the new challenge-response pair of the vehicle
(C#, K#), and the new pseudo-ID P I DV. If any hijacker
tries to tamper with the aggregator device, its PUF will be
destroyed and the protocol will not proceed to this stage.
Therefore, the adversary will not be able to access the new
In this section, we formally show that our MA protocol is
secure. We use Mao and Boyd logic [42] which is extensively
used for security analysis of protocols. In our analysis, we
denote vehicle IDV, aggregator I DM, and the grid server by
V,M, and G, respectively.
A. Mao-Boyd Logic
The basic building blocks of Mao-Boyd Logic listed below
are necessary to understand the protocol verification.
1) A B:Abelieves Bis legitimate and that it may
function correspondingly.
2) A
|B:Aencrypted Busing key K.
3) AK
/ B:Asees Busing decipherment key K.
4) AK
B:Kis a valid shared key between entities Aand
5) #(N): Nonce Nis new and fresh.
6) sup(P):Pis a credible and reliable entity.
7) A/ kM: Entity Adoes not have access to message M.
In our proof we use several inference rules of Mao and Boyd
logic which are listed in Table II. In the rules, ‘V’ represents
the logical AND of two statements. If P,Qare statements,
and the inference of their logical AND is statement R, it is
written in Mao and Boyd logic as R
B. Security Analysis
First, let us consider the MA between an aggregator and
the power grid server. We first prove the statement “Mis
convinced NBis a valid shared key between Mand G”. The
following proof is summarized in Mao and Boyd logic in Fig.
4a. The challenge-response pair of M,(C, K)is stored in
G, therefore it can be said that “Mand Ghave a well-kept
secret K”. In Mao and Boyd logic, this is written as shown in
equation (i). Using K, the aggregator is able to decipher the
variable Min message 3 of the protocol and obtain NBand
NI. Therefore, “Msees NIwith decipherment key K” which
is (ii) and “Msees NBwith decipherment key K” which is
/ NI(ii)
M G {M,G}c/kNB
VM G {M}c/kNBV
VM sup(G)
VM sup(G)V
(a) Proof for: “Mis convinced that NBas a valid shared key between Mand G”.
(b) Proof for: “Mis convinced that NCis
a valid shared key between Mand G”.
G M {M ,G}c/kNC
/ NB
VG M {G}c/kNCV
/ NC
VG sup(M)
(c) Proof for: “Gis convinced that NCis a valid shared key between Mand G”.
(d) Proof for: “Gis convinced that NBis
a valid shared key between Mand G”.
G M {M ,G}c/kK0
/ NB
VG M {G}c/kK0V
/ K0
VG sup(M)
(e) Proof for: “Gis convinced that K0is a valid shared key between Mand G”.
(f) Proof for: “Mis convinced that K0is
a valid shared key between Mand G”.
Fig. 4: Proof for authentication between aggregator and power grid server
V{V,M }c/kNA
V M {V ,M}c/kNA
V M V K00
V V K00
/ NV
VV M {V}c/kNAV
V V K00
/ NA
VV sup(M)
VV sup(M)V
(a) Proof for: “Vis convinced that NAas a valid shared key between Vand M”.
V{V,M }c/kNO
V V K00
(b) Proof for: “Vis convinced that NOis
a valid shared key between Vand M”.
M{V,M }c/kNO
M V {V ,M}c/kNO
M V V K00
M V K00
/ NA
VM V {M}c/kNOV
M V K00
/ NO
VM sup(V)
(c) Proof for: “Mis convinced that NOis a valid shared key between Vand M”.
M{V,M }c/kNA
M V K00
(d) Proof for: “Mis convinced that NAis
a valid shared key between Vand M”.
M V K#
M{V,M }c/kK#
M V {V ,M}c/kK#
M V V K00
M V K00
/ NA
VM V {M}c/kK#V
M V K00
/ K#
VM sup(V)
(e) Proof for: “Mis convinced that K#is a valid shared key between Vand M”.
V V K#
V{V,M }c/kK#
V V K00
(f) Proof for: “Vis convinced that K#is
a valid shared key between Vand M”.
Fig. 5: Proof for authentication between EV and aggregator
Name Inference Rule
Authentication rule
/ M
Nonce-verification rule
Confidentiality rule
Super-principal rule
P Q X VP sup(Q)
Intuitive rule P /M
/ M
Good Key rule
Fresh rule
Applying the authentication rule to statements (i) and (ii),
we obtain “Mbelieves Gencrypted NIusing key K” which
is (iii). Since Mgenerates a new nonce NIeach time, we
can say “Mbelieves NIis new and fresh” which is (iv). On
applying the nonce-verification rule to (iii) and (iv) we obtain
(v) which is “Mis convinced that Gis convinced that Kis
a well-kept secret between Mand G”.
We then apply authentication rule to (i) and (vi), to obtain
(vii) which is “Mis convinced that Gencrypted NBusing
K”. Since Ggenerates a new nonce NBeach time, Mis
knows that no one apart from Gcould have seen NB. Thus,
we have the statement “Mis convinced that Gis convinced
that no one other than Mhas access to NB” which is (viii).
Applying the confidentiality rule to (v), (vii) and (viii) we get
(ix) which states “Mis convinced that Gis convinced that no
one other than Mand Bhas access to NB”.
/ NB(vi)
M G {M}c/kNB(viii)
M G {M, G}c/kNB(ix)
It is assumed in the protocol that Gis a credible and reliable
entity and Mbelieves this as fact. Hence, the statement
Mbelieves that Gis a credible and reliable entity (super-
principal)” which is (x). Next, we apply the super-principal
rule to statements (ix) and (x), to obtain (xi) which is “Mis
convinced that no one other than Mand Ghas access to NB”.
To proceed further we need to understand a few definitions and
rules of message idealization from [42] which are discussed
in the Appendix.
In message 2 of the Fig. 2 Msends NIto G. As a response,
Gsends NBin message 3 by encrypting it inside variable
M. By deciphering variable M,Gobtains nonces NIand
NB. Therefore, according to the message idealization rules
presented in the appendix, NIcan be considered as a challenge
and NBcan be considered its response. Note that these are not
the same challenge-response pair (C, K)of the PUF. Thus we
arrive at the statement “Mcan see the replied challenge NI
and the response NBwith decipherment key K” which is (xii).
On applying the intuitive rule to (xii), we get (xiii) which is
Mcan see the replied challenge NIand the response NB”.
M sup(G)(x)
M{M, G}c/kNB(xi)
/ NIRNB(xii)
M / NIRNB(xiii)
We then apply the fresh rule to (iv) and (xiii), we obtain
statement (xiv) which is “Mbelieves NBis new and fresh”.
Finally, we apply the good-key rule to statements (x), (xi)
and (xiv) to prove the statement “Mis convinced that NBis
a valid shared key between Mand G”.
In a similar manner the proof for “Gis convinced that
NBis a valid shared key Mand G” is shown in Fig. 4d.
The statements “Mis convinced that NCis a valid shared
key between Mand G” and “Gis convinced that NCis
a valid shared key between Mand G” are shown in Fig.
4b and Fig. 4c respectively. The statements “Mis convinced
that K0is a valid secret key between Mand G” and “Gis
convinced that K0is a valid secret key between Mand G” are
shown in Fig. 4f and Fig. 4e respectively. In these figures, the
logical AND operation between two statements is represented
by a ‘V’. Thus, we have shown that an adversary cannot see
NB,NCor K0. The three variables NB,NCand K0are
critical because without them an adversary cannot decipher the
communicated data. The Mao Boyd formal proof discussed
above has proven the secrecy of NB,NCand K0which is
regardless of the kind of attack used by the adversary such
as man-in-the-middle (MITM) attack, masquerade attack, or
replay attack. In a very similar manner, the Mao and Boyd
logic proofs for the MA between the EV and the aggregator
can be obtained to establish that the critical variables of this
stage, i.e, NA,NOand K00 cannot be obtained by an adversary,
the proofs of which are shown in Fig. 5a - 5f. Note that
even if an attacker physically hijacks the aggregator or the
EV, by virtue of the property of PUF discussed in section I,
it is ensured that the adversary cannot obtain the legitimate
challenge-response pairs. Additionally, there are no secrets
stored on the aggregator or the EV itself. Thus, physical
security and protection against node tampering attack are also
guaranteed. Untraceablity is ensured by using a pseudo-ID,
P I DVas shown in Fig. 3.
The parameters used in generating the session key Skare
K0,NBand NCand the parameters used in generating session
key Sk2are K00
0,NAand NO. The nonces NB,NC,NAand
NOare cryptographic nonces which are randomly generated in
every session. As already discussed in section VI, the freshness
of the nonce is a necessary condition which is checked at
several stages of the MA protocol. Unless freshness is verified,
MA does not take place. In addition, the challenge response
pairs used in the protocol (C, K),(C0, K0),(C, K ”) and
(C#, K#)are all randomly generated. First a challenge is
randomly generated and its corresponding PUF response is
obtained. The output of a PUF depends both on the physical
disorder as well as the applied challenge, hence the response
obtained for each challenge will not only be random, but also
very different from each other. Therefore K0and K00
change randomly in each authentication round. The combined
effect of the randomness of these variables and the non-
linearity of the function Fguarantee that a unique session
key is obtained in each round for both stages of the protocol.
A. Security Goals And Protection Against Various Attacks
A comparison of the security features of our protocol with
a different state of the art protocols currently in use in V2G
systems is presented in Table III. “3” indicates that the
protocol possesses a feature or is secure against an attack. A
blank indicates that the protocol lacks a feature or is insecure
against an attack. All the mentioned protocols provide MA
except [24]. Without MA, a participating entity can neither
verify if it is sending a message to a trusted entity, nor can
it verify if the message it received is from a trusted entity.
With MA, both the sending and receiving parties can be
sure of each other’s authenticity. Identity protection is not
provided by the protocol in [23]. Consequently, an attacker
may easily figure out the real identity of the EV by looking
at the usage data. The protocols in [20] and [22] do not
provide message integrity. Our protocol uses MAC to ensure
this. All the entities (EVs, aggregators and grid server) can
easily detect any tampering in the messages they receive. The
protocol in [20] is vulnerable to man-in-the-middle attacks. An
adversary may insert itself between the communication of an
EV and the aggregator, or between the aggregator and the grid
server and gain control of the communication between them.
The protocols in [19], [20] and [22] are vulnerable against
impersonation attacks. The protocols in [20] and [22] are not
secure against replay attacks. The protocols in [20] and [23] do
not provide session key security. Physical security is provided
only by the proposed protocol (SUKA). As mentioned in
Section V-B, an attacker that captures an EV device must
not be able to gather any secrets. As also mentioned in
Section I, almost all authentication protocols proposed in the
literature require that the EVs store at least one secret in their
memory, if not more. Such storing of secrets on any device
renders the protocols vulnerable to physical attacks. The MA
protocol proposed in this paper has two features which make it
resistant to any physical attacks: (i) EVs and aggregators need
not store any secrets in their memory; (ii) there is a secure
communication between the EV’s microcontroller and its PUF
since they are both on the same chip [43]. Thus, even though
an attacker may physically capture the device, it would be
impossible for them to extract any secrets. Therefore, SUKA
is resilient against physical attacks. The papers in [19], [20]
[22], [24] and [31] do not provide a formal security proof for
their proposed protocols.
B. Computation Overhead
In Table IV, we present a comparison of the computation
costs of our protocol with some state-of-the-art protocols
which have a similar system model as ours. The comparison
is for the case where one EV is authenticating with the grid.
The number of cryptographic operations, pairing operations,
encryption/decryption, hash operations, MAC computations
and PUF executions are listed for one round of authentication,
setting m= 3. Our protocol uses only 33 cryptographic
operations (which include XOR, addition, scalar multiplication
and exponential computation) compared to 37 in [30] and 36 in
[20]. Our protocol uses zero pairing operations. While [20] has
only 2 encryption/decryption operations and 4 MAC/HMAC
computations, it has 9 hash function computations while
ours has zero. Although [30] has no encryption/decryption
operations or MAC/HMAC computations, it has 16 hash
computations while ours has none. While there is no physical
security in [19], [20] and [30], our protocol is physically
secured by the use of PUFs, which requires 2 operations. We
argue that the overall performance of our protocol is much
better due to lesser computation overhead and far superior
security features.
C. Performance Comparison
We simulated the operations carried out by an EV in the
security schemes of [19], [30] and [20], all of which have a
similar system model as SUKA. The simulations were carried
out in Python 2.7 on a PC with Intel Core i5-5200U processor
with 8GB DDR3 RAM. Fig. 6, shows the time consumed by
the EV in every round of authentication in the considered
schemes. The EV consumes 3.682 ms, 3.072 ms, 2.022 ms
in the security schemes of [19], [30] and [20] respectively
whereas only 0.845 ms in SUKA. Therefore, SUKA is more
efficient than state-of-the-art security schemes.
TABLE III: Comparison of Security Features
Features [18] [19] [20] [22] [23] [24] [31] SUKA
Mutual Authentication 33333 33
Identity Protection 3 3 3 3 3 3 3
Message Integrity 3 3 3 3 3 3
Man-In-The-Middle Attack 33 33333
Impersonation Attack 3 3 3 3 3
Replay Attack 3 3 3 3 3 3
Session Key Security 3 3 3 3 3 3
Physical Security 3
Formal Security Proof 3 3 3
TABLE IV: Comparison of computation overhead
Operations [19] [20] [30] SUKA
Cryptographic operations
(, +, scalar multiplication
and exponent)
81 36 37 33
Pairing 19 - - -
Encryption/Decryption - 2 - 6
Hash (H) 6 9 16 -
MAC/HMAC 7 4 - 8
PUF - - - 2
[19] [30] [20] SUKA
Schemes Considered
Time Consumed (in seconds)
Fig. 6: Comparison of time consumed by EV for MA in SUKA
and the security schemes of [19], [30] and [20].
This paper proposed MA protocols for the two stages or
steps which arise in a V2G system: (i) For MA between
the aggregator and the grid server, and (ii) for MA between
EV and aggregator. The proposed protocol (SUKA) uses a
challenge-response architecture, which is enabled by PUFs.
This gives our proposed protocol the advantage of not having
to store any secret information in EVs and aggregators. Secrets
are stored only in the grid server. Only one challenge-response
pair is stored in the server for every EV. Two session keys are
established when an EV wants to authenticate with the grid
server: one session key between the aggregator and the grid
server, and another one between the EV and the aggregator. We
showed that SUKA achieves MA, identity protection, message
integrity, physical security, and session key security along
with protection against various attacks such as MITM attacks,
replay attacks and impersonation attacks. SUKA is proven
formally secure by Mao and Boyd logic and uses simple
computations, which makes it very efficient and fast. Hence,
the proposed protocol is a viable solution for upcoming V2G
This research was supported in part by Singapore Ministry
of Education Academic Research Fund Tier 1 (R-263-000-
A. Rules of Message Idealization
A message without any symbols is called an atomic
message (AM).
If an AM is sent at one stage of the protocol by a node
and received by the same node in another stage of the
protocol, it is called a challenge.
Achallenge sent to its originating node is called a replied
If an AM and a response are sent together by a single
node for the first time, it is called a response.
AMs which are not challenges or responses are treated as
nonsense and are discarded.
In case an AM qualifies as a challenge and response in a
single line, it is considered a response.
Areplied challenge and its response together is denoted
as Response RRC.
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Gaurang Bansal received the B.E. & M.E. de-
gree in Computer Science from Birla Institute of
Technology and Science, Pilani, India, in 2018
and 2020 respectively. He has authored more than
10 publications in top tier confences and Journals
IEEE Transaction on Vehicular Technology, IEEE
Systems Journal. His research interests include the
IoT security, network security and distributed com-
Naren is currently pursuing his B.E in Electri-
cal and Electronics Engineering, and M.Sc (Hons)
in Physics with the Birla Institute of Technology
and Science (Pilani). He has completed projects on
Quark-Gluon Plasma, Superconductivity, hardware
security techniques in IoT and electromagnetic radi-
ation pollution. His other research interests include
IoT, Industry 4.0, and security provisioning in V2G,
UAV and Medical IoT networks.
Vinay Chamola received the B.E. degree in elec-
trical and electronics engineering and master’s de-
gree in communication engineering from the Birla
Institute of Technology and Science, Pilani, India, in
2010 and 2013, respectively. He received his Ph.D.
degree in electrical and computer engineering from
the National University of Singapore, Singapore, in
2016. In 2015, he was a Visiting Researcher with the
Autonomous Networks Research Group (ANRG),
University of Southern California, Los Angeles, CA,
USA. He also worked as a post-doctoral research
fellow at the National University of Singapore, Singapore where he worked
in the area of Internet of Things. He is currently Assistant Professor with
the Department of Electrical and Electronics Engineering, BITS-Pilani, Pilani
Campus where he heads the Internet of Things Research Group / Lab. He
has over 45 publications in high ranked SCI Journals including more than
25 IEEE Transaction and Journal articles. His works have been published in
Journals like IEEE Transactions on Communications,IEEE Transactions on
Vehicular Technology,IEEE Journal on Selected Areas in Communications,
IEEE Communications Magazine etc. Furthermore, his works have been
accepted and presented in reputed conferences like IEEE INFOCOM, IEEE
GLOBECOM, IEEE ICC, IEEE PerCom to name a few. His research interests
include IoT Security, Blockchain, 5G network management and addressing
research issues in VANETs and UAV networks. He has served as a reviewer
for several IEEE/Elsevier Journals. He is a Guest Editor in Computer
Communication, Elsevier. He also serves as an Associate Editor for the IET
Quantum Communications and Frontiers in Communications and Networks.
Biplab Sikdar (S’98–M’02–SM’09) received the
B.Tech. degree in electronics and communication
engineering from North Eastern Hill University,
Shillong, India, in 1996, the M.Tech. degree in
electrical engineering from the Indian Institute of
Technology Kanpur, Kanpur, India, in 1998, and the
Ph.D. degree in electrical engineering from Rensse-
laer Polytechnic Institute, Troy, NY, USA, in 2001.
He is currently an Associate Professor with the
Department of Electrical and Computer Engineering,
National University of Singapore, Singapore. His
current research interests include wireless network, and security for Internet of
Things and cyberphysical systems. Dr. Sikdar served as an Associate Editor for
He currently serves as an Associate Editor for the IEEE TRANSACTIONS
Neeraj Kumar received the Ph.D. degree in com-
puter science and engineering from Shri Mata
Vaishno Devi University, Katra, India. He is cur-
rently with the Department of Computer Science and
Engineering, Thapar University, Patiala, India. He
has authored or coauthored more than 300 technical
research papers in leading journals such as the IEEE
WORK MAGAZINE, and conferences. His research interests include mo-
bile computing, parallel/distributed computing, multiagent systems, service-
oriented computing, routing and security issues in mobile ad hoc, and sensor
and mesh networks.
Mohsen Guizani (S’85–M’89–SM’99–F’09) re-
ceived the B.S. (with distinction) and M.S. degrees
in electrical engineering, the M.S. and Ph.D. degrees
in computer engineering from Syracuse University,
Syracuse, NY, USA, in 1984, 1986, 1987, and
1990, respectively. He is currently a Professor at the
Computer Science and Engineering Department in
Qatar University, Qatar. Previously, he served in dif-
ferent academic and administrative positions at the
University of Idaho, Western Michigan University,
University of West Florida, University of Missouri-
Kansas City, University of Colorado-Boulder, and Syracuse University. His
research interests include wireless communications and mobile computing,
computer networks, mobile cloud computing, security, and smart grid. He
is currently the Editor-in-Chief of the IEEE Network Magazine, and the
Founder and Editor-in-Chief of Wireless Communications and Mobile Com-
puting journal (Wiley). He is the author of nine books and more than 500
publications in refereed journals and conferences. He received the 2017 IEEE
Communications Society WTC Recognition Award as well as the 2018 AdHoc
Technical Committee Recognition Award for his contribution to outstanding
research in wireless communications and Ad-Hoc Sensor networks. He was
the Chair of the IEEE Communications Society Wireless Technical Committee
and the Chair of the TAOS Technical Committee. He served as the IEEE
Computer Society Distinguished Speaker and is currently the IEEE ComSoc
Distinguished Lecturer. He is a Fellow of IEEE and a Senior Member of
... Gope and sikdar [19] proposed another lightweight protocol for a smart grid environment by employing one-way noncollision hash functions. In recent years, authors have thought about the physical security of devices in a smart grid environment and proposed protocols to protect their communications [8]- [10], [20]. Badar et al. [10] suggested a security protocol for a smart grid environment with power line surveillance, and it can secure data transfer between smart meters and service providers. ...
... Similarly, all protocols [4]- [10] except gope et al. [11], [12]'s protocols are suffering with physical attacks. Additionally, all protocols [4]- [6], [10], [11] provides user anonymity except [7], [8]'s protocols. The protocols [5] and [6] are fail to provide protection against man in the middle attack. ...
... The total amount of communication between the EV and CS i is therefore 272 bytes (128+80+64). According to Table VI, the current related protocols [4], [5], [6], [7], [8], [9], [10], [11], [12], require 280 bytes, 304 bytes, 464 bytes, 516 bytes, 448 bytes, 208 bytes, 336 bytes, 208 bytes, 208 bytes respetively. It is clear that the proposed protocol requires slightly more communication costs than the Gope et al. [9], [11], [12] protocols. ...
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Electric vehicle (EV) is a fast-growing technology that could help reduce greenhouse gas emissions in the energy and transportation sectors. The characteristics of EVs allow for rapid smart city expansion and serve as a key weapon in the emergence of vehicle-to-grid (V2G) technology. The entities, such as EVs and charging stations, connect with one another in order to gather data about the status of the EV and the environment in which it is traveling. The exchange of information among entities in V2G over a public channel may be exposed to security threats. The user's devices are also vulnerable to physical attacks since they are left unprotected at their end. Hence, we suggest a lightweight protocol for key agreement and mutual authentication between entities operating in a V2G environment. Additionally, we assess the proposed scheme using the Scyther tool to conduct formal and informal security analyses in order to demonstrate how effectively it can counteract known security attacks. Finally, the performance study reveals that the suggested protocol provides a communication and computational benefit when compared to relevant protocols.
... Table 3 and Table 4 review authentication protocols in V2G charging, also elaborate merit and demerit of existing works. Bansal et al. [35] proposed a lightweight authentication and key agreement protocol based on physically uncloneable function (PUF) for V2G. Firstly, the challenge response and key agreement are applied to achieve mutual authentication and prevent the aggregator from being captured, respectively. ...
... For distributed charging, in the home mode, the EV authenticates home CA through home aggregator. In the multi-visiting mode, to prevent the attacker A lightweight authentication and key agreement protocol [35] • PUF ...
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In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.
... The manufacturing process of the PUF in each UAV is the same, but due to the tiny random changes inherent in the manufacturing process, the output of each function is different [11]; that is, PUF is used to make each UAV have its own fingerprint. This fingerprint cannot be cloned, because PUF is unclonable, and it is impossible to make two identical functions [12]. Furthermore, the adversary captures an UAV and enters a challenge into the PUF in the UAV. ...
... Note: FE 1 : replay attack; FE 2 : man-in-the-middle attack; FE 3 : device impersonation attack; FE 4 : device capture attack; FE 5 : privileged insider attack; FE 6 : private key leakage attack of control room or ground station server; FE 7 : session key forward and backward secrecy; FE 8 : mutual authentication; FE 9 : key agreement; FE 10 : support dynamic device addition; FE 11 : provide formal security verification by using AVISPA tool. √: a scheme resists an attack, or it supports a function; ×: a scheme does not resist an attack, or it does not support a function.12 Wireless Communications and Mobile Computing configuration of the UAV and communication module, and the last difficulty is the shortage of spectrum resources. ...
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Nowadays, unmanned aerial vehicles (UAVs) are used in various fields due to their high maneuverability and low cost of construction and use. With the development of UAV technology, it has become a trend for UAVs to cooperate with each other to complete assigned tasks. Multiple UAVs are combined according to a certain structure, and through the information sharing between them, a cooperative effect is generated to achieve intelligent collaborative task execution. However, information sharing is carried out on a public channel, so ensuring secure communication between UAVs is crucial. Moreover, UAVs are easily captured by an adversary, who can impersonate legitimate UAVs to disrupt communications if UAVs’ internal secrets that are stolen. Therefore, we propose a lightweight authentication scheme based on physical unclonable function (PUF), to provide mutual authentication between UAVs. PUF is embedded in the unmanned aerial vehicle (UAV) to defend against physical capture attack. Furthermore, to evaluate the security and performance of our scheme, formal and informal security analyses and formal security verification of the scheme are performed, and the performance of the scheme is compared with existing UAV schemes. The above analyses show that our scheme has great advantages in terms of security and overheads.
... Physical Uncloneable Functions (PUFs) have been explored as a way to prevent physical attacks. They have been used in PUF-based protocols for various applications, including RFIDs [11], electric vehicles [12], and IoT sensor nodes [13]. Aman et al. [14] proposed a PUF-based protocol that is resilient to physical attacks on IoT devices, in the IoT-Cloud architecture. ...
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The IoT-edge-cloud paradigm enables resource-constrained IoT devices to offload their computation, thereby meeting the required quality-of-service for real-time applications. However, the deployment of IoT devices in public places such as smart cities exposes them to various security threats, including physical attacks. To address these security concerns, we propose a Physical Unclonable Function (PUF) based IoT-edge-cloud Symmetric Key Authentication protocol with Forward Secrecy (), which ensures the anonymity of transacting IoT devices, resilience to desynchronization-based denial-of-service attacks, and PUF modeling attacks. To evaluate the security of our protocol, we conduct a formal security analysis using the automated AVISPA tool. In addition, based on the indistinguishability property of the PUF, we formally prove that is secure under the CK-adversary model. Moreover, we implement the protocol using socket programming between a Raspberry Pi 1 as an IoT device, a Raspberry Pi 4 as an IoT gateway, and an 11th Gen Intel Core i7-11800H laptop as the CA to simulate the message flow between the protocol entities in a real-time experiment and calculate its end-to-end latency. Finally, we compare with other PUF-based protocols in terms of computation time, communication cost, and storage requirements.
... Regarding physical security, several authentication protocols based on Physical Unclonable Function (PUF) have been proposed [29][30][31][32][33]. The inherent unclonable function makes PUF a physical one-way function suitable as physical security primitives [34,35]. ...
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The Space–Air–Ground Integrated Network (SAGIN) expands cyberspace greatly. Dynamic network architecture, complex communication links, limited resources, and diverse environments make SAGIN’s authentication and key distribution much more difficult. Public key cryptography is a better choice for terminals to access SAGIN dynamically, but it is time-consuming. The semiconductor superlattice (SSL) is a strong Physical Unclonable Function (PUF) to be the hardware root of security, and the matched SSL pairs can achieve full entropy key distribution through an insecure public channel. Thus, an access authentication and key distribution scheme is proposed. The inherent security of SSL makes the authentication and key distribution spontaneously achieved without a key management burden and solves the assumption that excellent performance is based on pre-shared symmetric keys. The proposed scheme achieves the intended authentication, confidentiality, integrity, and forward security, which can defend against masquerade attacks, replay attacks, and man-in-the-middle attacks. The formal security analysis substantiates the security goal. The performance evaluation results confirm that the proposed protocols have an obvious advantage over the elliptic curve or bilinear pairings-based protocols. Compared with the protocols based on the pre-distributed symmetric key, our scheme shows unconditional security and dynamic key management with the same level performance.
The popularity of Electric Vehicles (EVs) has been rising globally in recent years. With the demand for EVs, associated cyber threats are also increasing. Users expose their personal information while charging their EVs, leading to privacy threats. This article proposes a user-empowered, privacy-aware, authenticated key exchange protocol for Vehicle-to-Grid (V2G) communications. The proposed protocol leverages the concept of Self-Sovereign Identity (SSI) and is based on the concept of Decentralized Identifiers (DID) and Verifiable Credentials (VCs). The use of DIDs empowers users by helping them to have complete control over their identities. The charging station and the user verify that the other party is legitimate by verifying the VC before proceeding with the charging services. Key recovery is another issue we address in this article. A method to recover lost keys is incorporated into the proposed protocol. The proposed protocol also incorporates an effective user revocation policy. We present formal security proof and informal analysis to show the protocol's robustness against several attacks. We also provide a detailed performance analysis to show that the proposed protocol is efficient.
Conference Paper
Due to the recent emerging trends in technology, Vehicle to Grid (V2G) networks plays a major role in smart grid system. Now a days using of electric vehicles has increased than the usage of fuel-based automobiles under transportation. Electric vehicles mainly use electricity instead of fuels that is distributed by the charging terminal. Generally, the charging terminal will be situated in gasoline stations or on road sides and electric vehicles get charged at the stations. In V2G communication networks, the communication takes place between the charging terminal and the electric vehicle will be affected by several cyber-attacks. In addition to that, the electric vehicle owner’s personal information should be kept secure. In this proposed system, charging terminal and electric vehicles initially register their identities at the control authority. Using of Anonymous mutual authentication scheme, the charging terminal and the electric vehicle authenticates with each other and establish protected communication between them. During Session Key Exchange protocol, the information passed from the charging terminal will be transferred to the electric vehicle with the help of session keys. Duplicate identity of the charging terminal and electric vehicle is created in order to protect the original identity of the users who are present in V2G networks. Proposed scheme gives strength against various security attacks and cost of the system is also reduced. The main aim of this proposed system is to maintain confidentiality and integrity among the V2G communication networks.
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As consumer Internet of Things (IoT) devices become increasingly pervasive in our society, there is a need to understand the underpinning security risks. Therefore, in this paper, we describe the common attacks faced by consumer IoT devices and suggest potential mitigation strategies. We hope that the findings presented in this paper will inform the future design of IoT devices.
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The notion of aggregation of data in IIoT environment is a common practice. It shortens the data and associated signatures to reduce the bandwidth requirement. The compact aggregate signature (CAS) scheme creates a constant length aggregate signature (AS). Thus, the length of the CAS is independent of the number of messages or signatures to be aggregated. This article presents the first pairing free compact aggregate signature scheme in certificate-based settings. Due to the certificate-based approach, the proposed scheme is free from key escrow and key distribution problems inherited in identity-based cryptography (IDC) and certificate-less cryptography (CLC) respectively. Being compact and pairing free, it is the least bandwidth-consuming and the most efficient provably secure aggregation method. The length and computational cost analysis show that the scheme is the most appealing to use in the IIoT environment.
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Internet of things (IoT) is the next era of communication. Using IoT, physical objects can be empowered to create, receive and exchange data in a seamless manner. Various IoT applications focus on automating different tasks and are trying to empower the inanimate physical objects to act without any human intervention. The existing and upcoming IoT applications are highly promising to increase the level of comfort, efficiency, and automation for the users. To be able to implement such a world in an ever growing fashion requires high security, privacy, authentication, and recovery from attacks. In this regard, it is imperative to make the required changes in the architecture of IoT applications for achieving end-to-end secure IoT environments. In this paper, a detailed review of the security-related challenges and sources of threat in IoT applications is presented. After discussing the security issues, various emerging and existing technologies focused on achieving a high degree of trust in IoT applications are discussed. Four different technologies: Blockchain, fog computing, edge computing, and machine learning to increase the level of security in IoT are discussed.
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This paper introduces a new design methodology for incorporating process-sensitive optical nanostructures in standard CMOS processes to create robust optical physically unclonable functions (PUFs) realized through an electrical-photonic co-design approach. The passive lithographic variations of lower level metal interconnects are exploited to realize resonant photonic crystals on an array of photodetectors to include variations that are robust to noise processes. The chip is realized in a standard 65-nm CMOS process with no additional post-processing. The addition of the structures increases the coefficient of variation by a factor of 3.5x compared to only active device variations. This creates extremely robust PUF responses with a native inter-chip Hamming distance (HD) of 49.81% and intra-chip HD of 0.251% with an inter-HD/intra-HD ratio of 198x illustrating the reliability of the design. The native intra-HD can be reduced to 0.06% with 17 mV of thresholding with only 4% of the total combinations discarded. To the best our knowledge, this is also the first demonstration of photonic crystals and an optical PUF in CMOS.
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Smart vehicle-to-grid (V2G) involves intelligent charge and discharge decisions based on user operational energy requirements, such as desired levels of charging and waiting time. V2G is also supported by information management capabilities enabled by a secure network, such as a reliable privacy-preserving payment system. In this article, we describe the network security and privacy requirements and challenges of V2G applications. We present a new network security architecture to support V2G. We propose a scheme with the following security and privacy-preserving features: anonymous authentication, fine-grained access control, anonymous signatures, information confidentiality, message integrity, remote attestation, and a payment system. This article is oriented toward practitioners interested in designing and implementing secure and privacy-preserving networks for smart V2G applications.
This paper presents a physically unclonable function (PUF) based on the randomness of soft gate oxide breakdown (BD) locations in MOSFETs, namely, soft-BD PUF . The proposed PUF circuit features a self-limiting mechanism that generates exactly one soft-BD spot in a pair of NMOS transistors. Highly stable “0” and “1” bits with an equal probability of 0.5 are extracted based on the locations of the generated BDs. A differential readout scheme is employed based on the proposed reference-free sense amplifier (SA), resulting in good current sensitivity and side-channel attack resilience. The soft-BD PUF, fabricated in a 40-nm CMOS process, comprises all essential periphery circuits. Measurements show that the soft-BD PUF has good data stability in a wide operating range. The native bit error rate is 0% for $V_{\text {DD}}=1\,\,\text {V}$ and above, shown by measuring 10k readout cycles among 10k PUF cells. Data stability degrades at lower supply voltage and higher temperature due to the conductivity of PUF cells and the offset of SAs. Under the nominal $V_{\textrm {DD}}$ of 0.9 V in this technology, the throughput is shown to be at least 40 Mb/s and the PUF readout consumes only 51.8 fJ/bit. The averaged hamming weight and hamming distance are 0.497 and 0.496, respectively, showing a good randomness and uniqueness. The resulting PUF data show good statistical properties by passing all the relevant tests in the NIST 800-22 suite.
The concept of smart metering allows real-time measurement of power demand which in turn is expected to result in more efficient energy use and better load balancing. However, finely granular measurements reported by smart meters can lead to starkly increased exposure of sensitive information, including various personal attributes and activities. Even though several security solutions have been proposed in recent years to address this issue, most of the existing solutions are based on publickey cryptographic primitives such as homomorphic encryption, elliptic curve digital signature algorithms (ECDSA), etc. which are ill-suited for the resource constrained smart meters. On the other hand, to address the computational inefficiency issue, some masking-based solutions have been proposed. However, these schemes cannot ensure some of the imperative security properties such as consumer’s privacy, sender authentication, etc. In this paper, we first propose a lightweight and privacyfriendly masking-based spatial data aggregation scheme for secure forecasting of power demand in smart grids. Our scheme only uses lightweight cryptographic primitives such as hash functions, exclusive-OR operations, etc. Subsequently, we propose a secure billing solution for smart grids. As compared to existing solutions, our scheme is simple and can ensure better privacy protection and computational efficiency, which are essential for smart grids.
Embedded systems play a crucial role in fueling the growth of the Internet-of-Things (IoT) in application domains such as healthcare, home automation, transportation, etc. However, their increasingly network-connected nature, coupled with their ability to access potentially sensitive/confidential information, has given rise to many security and privacy concerns. An additional challenge is the growing number of counterfeit components in these devices, resulting in serious reliability and financial implications. Physically Unclonable Functions (PUFs) are a promising security primitive to help address these concerns. Memory-based PUFs are particularly attractive as they require minimal or no additional hardware for their operation. However, current memory-based PUFs utilize only a single memory technology for constructing the PUF, which has several disadvantages including making them vulnerable to security attacks. In this paper, we propose the design of a new memory-based combination PUF that intelligently combines two memory technologies, SRAM and DRAM, to overcome these shortcomings. The proposed combination PUF exhibits high entropy, supports a large number of challenge-response pairs, and is intrinsically reconfigurable. We have implemented the proposed combination PUF using a Terasic TR4-230 FPGA board and several off-the-shelf SRAMs and DRAMs. Experimental results demonstrate substantial improvements over current memory-based PUFs including the ability to resist various attacks. Extensive authentication tests across a wide temperature range (20 - 60 deg. Celsius) and accelerated aging (12 months) demonstrate the robustness of the proposed design, which achieves a 100% true-positive rate and 0% false-positive rate for authentication across these parameter ranges.
The concept of the Social Internet of Things (SIoT) can be viewed as the integration of prevailing social networking and the Internet of Things (IoT), which is making inroads into the daily operation of many industries. Smart grids, which are cost-effective and environmentally-friendly applications, are a promising field of the SIoT. However, security and privacy concerns are the dark aspects of smart grids. The goal of this paper is to address the security and privacy issues in the vehicle-to-grid (V2G) networks with the intention of promoting a more extensive deployment of V2G networks for smart grids. Driven by this motivation, in this paper, we propose a robust key agreement protocol that can achieve mutual authentication without exposing the real identities of users. Efficiency is also a major concern in resource-constrained environments. By leveraging only hash functions and bitwise exclusive-OR (XOR) operations, the proposed protocol is highly efficient compared with pairing-based protocols. In addition, we define a formal security model for our privacy-preserving key agreement protocol for V2G networks. Using this model, a formal security analysis shows that the proposed protocol is secure. Moreover, an informal security analysis demonstrates that our protocol can withstand different types of attacks.
Vehicle-to-Grid (V2G) systems promoted by the federated Internet of Things (IoT) technology will be ubiquitous in the future; therefore, it is crucial to provide trusted, flexible and efficient operations for V2G services using high-quality measures for security and privacy. These can be achieved by access and authority authentication. This paper presents a lightweight protocol for capacity-based security access authentication named AccessAuth. Considering the overload probability and system capacity constraints of the V2G network domain, as well as the mobility of electric vehicles, the ideal number of admissible access requests is first calculated adaptively for each V2G network domain to actively achieve capacity-based access admission control. Subsequently, to provide mutual authentication and maintain the data privacy of admitted sessions, by considering whether there is prior knowledge of the trust relationship between the relevant V2G network domains, a high-level authentication model with specific authentication procedures is presented to enforce strict access authentication such that the sessions are conducted only by authorized requesters. Additionally, efficient session revocation with forward security and session recovery with no extra authentication delay are also discussed. Finally, analytical and evaluation results are presented to demonstrate the performance of AccessAuth.