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On The Possibilities of Cybercrime in IoT Devices

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Internet of Things (IoT) has been augmenting the emerging technologies and certainly been varying our daily life. The adoption of this technology is strengthened by the growth of connecting devices as shown in recent literature. However, responsibility related to secure communication also needs to increase as the number of connections grows. For instance, cybercrime might happen if simple topology and protocol are not implemented on IoT applications, or the communications from sensors to the Internet are weakly defined. This research reviews the vulnerability of existing topology and configuration on IoT. A secure communication is proposed between sensor nodes and the Internet. Further, this research demonstrates the feasibility of recommended protocol communication for several IoT devices through real testbed for smart home.
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On The Possibilities of Cybercrime in IoT Devices
1Yosafat Marselino Agus, 2Muhammad Dzakwan Falih, 3Gandeva Bayu Satrya
1 School of Electrical Engineering, Telkom University, Republic of Indonesia
2,3School of Applied Science, Telkom University, Republic of Indonesia
1ninoagus@protonmail.com, 2dzakwan@ieee.org, 3gbs@telkomuniversity.ac.id
Article Info
Volume 83
Page Number: 8231 - 8238
Publication Issue:
March - April 2020
Article History
Article Received: 24 July 2019
Revised: 12 September 2019
Accepted: 15 February 2020
Publication: 09 April 2020
Abstract
Internet of Things (IoT) has been augmenting the emerging technologies and certainly been
varying our daily life. The adoption of this technology is strengthened by the growth of
connecting devices as shown in recent literature. However, responsibility related to secure
communication also needs to increase as the number of connections grows. For instance,
cybercrime might happen if simple topology and protocol are not implemented on IoT
applications, or the communications from sensors to the Internet are weakly defined. This
research reviews the vulnerability of existing topology and configuration on IoT. A secure
communication is proposed between sensor nodes and the Internet. Further, this research
demonstrates the feasibility of recommended protocol communication for several IoT
devices through real testbed for smart home.
Index Terms; IoT, protocol, sensor nodes, secured communi-cation, vulnerability.
I. INTRODUCTION
Communication between smartphone devices or
sending commands to home devices is no longer a
fantasy with the development of future wireless
communication technology. Data communication
from machine to machine or human to machine
using Internet connection is called as Internet of
Things (IoT). IoT is one of the most important IT
tendencies and it is getting more appealing in home
or factory automa-tion. Figure. 1 illustrates an IoT
communication architecture consists of sensors,
smart objects, smart devices, gateways, back-end
data centers, and services [1].
Figure. 1: IoT system architecture
Data security and privacy certainly become the main
topics for any organization that is connected to the
Internet. On February 2018, the Interpol National
Central Bureau held a meeting in Vienna where 43
cybercrime investigators and digital forensics
experts were invited from 23 countries to investigate
cyberattack simulations on IoT devices [2]. They
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have given four guidance on how to secure
connected devices from cybercrime. The risks are
far greater on IoT because of much more personal
and important data collected from abundant IoT
devices that could be used for vicious intentions.
Thus, providing a suitable security control or
communication protocol for consumers has become
a necessity for IoT device vendors.
IoT needs to incorporate various sensor nodes or
smart objects, computer or server and wireless
connection, which are using different
communication protocols. Based on TCP/IP
protocol stack, several communication protocols
have been proposed on each layer. For this research,
it will focus on application layer. Observing last
recent research update related to application’s
protocol for IoT, five outstanding protocols are
HTTP [3], XMPP [4], MQTT [5], AMQP [6], and
CoAP
a) However, MQTT is the most candidates for
standard IoT communication protocols due to it
reduces protocol overheads and provides reliable
delivery of messages [8][10].
Researches in recent years focusing on IoT security
prob-lems aimed for different aspect. Commencing
with the survey by [11]] that proposed security
requirements specific to IoT systems by taking into
consideration network security, identity
management, privacy, trust, and resilience from
well-known standardization technology. Another
approach from [12] de-signed and implemented a
reliable message transmission sys-tem based on
MQTT Protocol for IoT devices. However,
[13] proposed a simple security framework for
MQTT (for short, AugMQTT) by incorporating the
AugPAKE protocol that gives security against
passive attacks, active attacks, and off-line
dictionary attacks. In the era of urban computing and
IoT systems, [14] identified three prominent
approaches to provide seamless and lightweight
IoTinteractions, high-lighting a representative,
standardized protocol for each of these approaches.
Acknowledging those literature, there are still many
available research areas that can be explored in
order to provide optimized topology, secure scheme,
or modest algorithm for IoT architecture.
Initiating with the deployment MQTT protocol for
IoT adopted from [10], this research shows that
vulnerability i.e. stealing data information can give a
serious hit. That reason brought this research to
optimization of MQTT protocol implementation in
IoT environment. By using that topology, the pen-
testing for deep investigations were successfully
con-ducted and developed secure end to end
communication from sensor nodes to back-end data
centers. The implementation and testing were
carried out using three Raspberry Pi 3B as IoT
devices, Mosquitto as MQTT broker, Eclipse Paho
library on Python for IoT, and Wireshark for
protocol analyzerThe contributions of this research
are as follows:
Proposing a secure topology by using MQTT over
web-socket where the unregistered IoT devices
might not connect.
Providing an optimized MQTT protocol
configuration based on the testbed by adding
lightweight cryptography from physical layer to
application layer.
Presenting a guidance for secure IoT device
topology by considering smart hospital, smart home,
smart factory, or other enhanced IoT technology
serving vital information.
The section II reviews existing works in IoT
security. While section III explains the proposed
scheme for secure end to end communication among
IoT devices. Then, the details of unsecure and
secure experiments are provided in section IV.
Finally, section V gives the conclusions of this
research.
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II. RELATED WORKS
Singh et al. proposed a secure version of MQTT and
MQTT-SN protocols (SMQTT and SMQTT-SN) in
which the security feature is augmented to the
existing MQTT protocol based on Key/Ciphertext
Policy-Attribute Based Encryption (KP/CP-ABE)
using lightweight Elliptic Curve Cryptography [15].
According to the theoretical and experimental
analysis, the proposed schemes showed better
performance than the scheme described in [3] which
was based on KP/CP-ABE. However, those
proposed schemes were just simulation-based and
has not yet been implemented on a real IoT
platform.
Dragomir et al. have done surveys in the last several
years to prevent attackers from obtaining control
over the IoT devices
1) Many solutions have been proposed by IoT
security researches in the last years, but most of
them were not standardized or interoperable. The
research evaluated security requirements specific to
IoT systems considering the network security,
identity management, privacy, trust, and resilience.
The results were summarized by functionality and
security capabilities and specified by standardization
bodies e.g., IETF, IEEE, or industry alliances.
Andy et al. discussed several reasons of many IoT
system that does not implement adequate security
mechanism. The research also demonstrated and
analyzed how to easily attack this protocol using
several attack scenarios [16]. Considering Shodan as
the problem identification, it showed that 24998
brokers who have connection code of "0" were
easier to be attacked because this kind of broker did
not use any client authentication mechanism. To the
best of authors’ knowledge, this paper just
concluded with a suggestion that MQTT pro-tocol
must be implemented e.g., TLS, ECC, or other
recent secured protocol on IoT devices.
Grgic´ et al. [17] proposed a web-based IoT solution
aimed for monitoring, tracking and analyzing data in
agriculture area. The research was done by installing
and connecting sensors to devices (e.g. Arduino
Uno, Raspberry Pi) which main task was to send
data (i.e. temperature and moisture values) to a
central server over MQTT. The results showed that
MQTT protocol has several characteristics i.e., low
overhead, asynchronous communication, low
complexity and low power.
Niruntasukrat et al. [18] presented design and
implemen-tation of an authorization mechanism by
using MQTT for IoT. The design was based on the
OAuth 1.0a, an open authorization standard for web
applications. Some redesign and modification have
been made to the base framework to make it fit
within the MQTT environment. However, the
authorization mechanism demanded two sets of
credentials for the device to access the MQTT
broker. Through experiments and real services, the
proposed authorization process worked as intended,
and the incurred overhead did not affect user’s
experiences.
III. PROPOSED FRAMEWORK
For the sake of completeness in securing
communication between the IoT devices, this
research implements MQTT as the prime candidate
from recent existing literature. Figure. 2a shows the
deployment of conventional MQTT implementation
for IoT topology or called as unsecured transaction
framework
[10]. The next section provides a deep investigation
for this topology. To the best of authors’ knowledge,
most of the simulation and evaluation of MQTT just
gave assurance on the protocol level from sensor
nodes to MQTT broker. But from adversary’s point
of view (unregistered sensor nodes), the data sensor
over web-socket still can be diagnosed with plain
text. For concealing this issue, this research suggests
adopting auto-keying between publishers and
subscribers to reject the unregistered sensor nodes.
Proposed IoT topology for securing end to end
communication from sensor nodes to web platform
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(HTTPS) or called secured transaction framework is
depicted in Figure. 2b.
A. Unsecured Transaction Framework
The implementation was deployed using two unit of
Rasp-berry Pi 3B as registered devices and one unit
as an un-registered device. The Wi-Fi connection
had medium access to MQTT Publisher. The
configuration for MQTT broker, MQTT subscriber,
and database server had been built by following the
MQTT library or documentation as can be seen in
Figure. 2a. This topology also provided HTTPS web
server for pooling the data’s sensor. The pen-testing
this topology are discussed in the following section.
MQTT is a topic-based publish/subscribe protocol.
Every message is published on a designated topic,
and every subscription has a topic filter that can
include wildcards. So, the authorization is in terms
of publishing/subscribing and topic designating.
The most common problem in implementing IoT
system based on MQTT protocol is the poorly
configured devices. The default configuration of
MQTT devices running on Mosquito service and
Paho MQTT library on Python enables the data with
unencrypted format to be transmitted over the
Internet. By imitating the format data and the topic,
some adversaries may spoof the broker’s and the
subscriber’s sides. Faking the data or crippling the
server is possible in this scenario. Upon this
hypothesis, further analysis will be addressed in the
next section.
(a) Conventional IoT topology using MQTT [10(b) Proposed secure web-socket IoT topology
Figure. 2: Comparison IoT architecture with optimized configuration by using MQTT protocol
B. Secured Transaction Framework
Slightly, there is no difference between the proposed
topol-ogy and the conventional IoT topology. As
shown in Fig-ure. 2b, this research recommends
lightweight cryptography algorithm for IoT devices
to camouflage the messages from sensor node to
web platform or to prevent the possibility of the
publisher’s data stealing (unregistered Raspberry Pi
device). The implementation of costumed Fernet
library at the publisher’s, broker’s, subscriber’s, and
web platform’s sides, the secure topology were
enforced to be more secure.
Fernet cryptography guarantees that a message, that
was encrypted by using it, cannot be manipulated or
read without the key. Fernet is categorized a
symmetric authenticated cryp-tography. This
research employs 128-bit AES and HMAC for the
authentication and modifies the Fernet to be more
robust in key rotation. Thus, the IoT devices were
authenticated and only the authorized devices with
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the key can publish and subscribe to a restricted
topic. This research hypothesizes that the proposed
topology could give protection from fake publishers,
fake devices, and invalid uses of data.
Algorithm 1 Autokeying Publisher Encryption
1 INITIALISE publisher_ID;
2 INITIALISE dataSensors_sent;
3 INITIALISE MQTT_connection;
4 passcode = HMAC "encoded_password_string";
5 final_key = derive (passcode);
6 while true do
7 ENCODE dataSensors_sent
8
8
:
˚
.
encrypted data
PUBLISH dαtαSϵnsϕrs_še¸ñt
9 end while
Algorithm 2 Autokeying Subscriber Decryption
1 INITIALISE subscriber_ID;
2 INITIALISE MQTT_connection;
3 INITIALISE final_key;
4 4: final_key =
generated_key_publisher; . from
publishers
5 while true do
6 SUBSCRIBE dαtαSϵnsϕrs_še¸ñ˚t
7 ˚
8
.
usingfinal_key
9 7:DECODE
dαtαSϵnsϕrs_še¸ñt
10 end while
1) Publisher Encryption Algorithm: The
publisher’s iden-tity that send data
(dataSensors_sent) is known. The publisher will
forward the data to the MQTT broker by using
MQTT connection. Upon sending a secret key to
one connection, the secret key will do HMAC for
each string of passwords that will be used on the
subscriber’s side as a guarantee of information
integrity. The same key generation method can be
used by all publishers, so the subscriber can decode
all of the incoming information with only one key.
The next process with the key is to encrypt the data
(dαtαSϵnsϕrs_še¸ñ˚t) sent by the publisher as
presented in Algorithm 1.
2) Subscriber Decryption Algorithm: It is known
that the identity of which subscriber will receive the
encrypted data from the publisher. Indeed, the
connection between the sub-scriber and the MQTT
broker has been established and the key of the
publisher (final_key) has been generated as
presented in Algorithm 2. Then, the incoming key
will be decrypted by using the key. If the format of
incoming data could not be recognized, then the
subscriber will reject the received data from
publisher. Moreover, the subscriber will get
encrypted data (dαtαSϵnsϕrs_še¸ñ˚t) which will then
be decrypted to be displayed on the web platform
IV. SECURITY ANALYSIS
A. Unsecured Transaction Experiment
Figures. 3 and 4 shows the results of network
analysis with topology as in section III is
successfully extracted. Certainly, MQTT has been
implemented properly which can be seen from the
Wireshark output below. Data from sensor node will
be sent to the web platform (HTTPS). Although the
broker and MQTT broker are secure, the data sent
via web-socket still can be seen (plain text).
Therefore, it can be concluded that it is not enough
for guaranteeing the data’s integrity only by
implementing the publisher node, MQTT broker,
and subscriber node. Next, the solution to this
problem will be explained.
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Figure. 3: Analyzing for the conventional
topology
Figure. 4: Captured packets from the
conventional topology
B. Secured Transaction Experiment
As seen in Figures. 5 and 6, the proposed IoT
topology is more secure in terms of data privacy.
The dataSensor_sent from the publisher was already
authenticated and encrypted by using base-64
format. Though Fernet cryptography is symmetric
encryption method, this problem was addressed by
using generate_key to keep rotating the secret key
for each data released by the publisher.
To the best of authors’ knowledge, it can also be
seen in Figure. 6 that the data are no longer
recognized as a plain text but a cipher text which
can also eliminate the possibility of attacks in data
integrity category.
Figure. 5: Analyzing for the secured topology
Figure. 6: Captured packets from the secured
topology
C. Discussion of Experiment
The proposed secure web-socket topology was
indeed proved to be twice bigger than the
conventional topology by examining data length
during the communication between publisher and
subscriber. Upon the product specification of
Raspberry Pi 3 Model B, the cryptography
computation of encrypted data for 180 bytes (as
depicted in Figure. 5) still can be addressed by Quad
Core 1.2GHz Broadcom BCM2837 64bit CPU. To
the best of authors’ knowledge, this proposed
topology should be implemented for future secure
end to end communication of IoT devices.
Based on the two experiment categories, the basic
con-figuration or features provided by vendors
should be given more attention during the
deployment of IoT devices. With the increasing
number of sensor nodes that will serve the
consumers, it is very important to ensure the security
of the network e.g., optimizing the configuration,
pen-testing the networks, and implementing third
party authentication. This research proposes auto-
keying either encryption or decryption in ensuring
integrity of the passing data (as shown in Figure. 6).
In accordance with the previous explanation, it is
proven that the proposed IoT topology is more
secure compared to conventional IoT topology
which only uses MQTT protocol.
V. CONCLUSION
In this research, the feasibility of MQTT were
implemented and analyzed to enable secure
communication for IoT devices with real testbed.
However, it also showed the drawback of MQTT
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protocol when the publisher sends the topic to
subscriber throughout web platform. As
recommendation, this research proposed a secure
web-socket IoT topology between publisher and
subscriber combined with MQTT protocol for IoT
devices. Moreover, this research also suggested the
use of encryption and decryption to enhance security
of end to end communication in the implementation
of smart hospital, smart home, smart factory, etc.
Further security analysis of secure web-socket for
IoT devices under different attack scenarios might
be considered. This tesbed research was based on
the internal threat, future research needs to
scrutinize the external threat and use different
vendor IoT devices.
VI. ACKNOWLEDGMENT
This research was collaborated between School of
Ap-plied Science and School of Electrical
Engineering, Telkom University. This research was
also funded by PPM, Telkom University.
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... For this stage, we developed a qualitative analysis of the 55 documents from the eligibility analysis phase using ATLAS TI version 9. During the qualitative analysis, 11 codes were defined in the Atlas TI associated with factor: application domain, related to the verticals in which IoT systems have been implemented [22][23][24]; attack surface, related to the entry and exit points via which attacks can be performed [25]; interdependency, related to the relationship of the IoT system with other IT/OT/IoT systems that could increase the severity of the attack [26]; scalability, related to the coverage area that can be affected by the propagation of the attack [27]; severity, related to the value of the damage that can be caused by the attack [28]; susceptibility, related to the predisposition to pick up the effects of an attack [29]; type of attack, related to the attack vector, technique or methodology [30,31]; device type, related to the type of IoT device [32,33]; type of information, related to the type of information processed, stored, or transmitted by the device [34]; uncertainty, related to the unknown factors that could affect the security of IoT systems [35]; vulnerabilities, related to the weak points that IoT systems may have and that may increase the possibility of being affected by an attack [36][37][38][39][40][41]. The density values of the codes (factors) are shown in Figure 4. ...
... For this stage, we developed a qualitative analysis of the 55 documents from the eligibility analysis phase using ATLAS TI version 9. During the qualitative analysis, 11 codes were defined in the Atlas TI associated with factor: application domain, related to the verticals in which IoT systems have been implemented [22][23][24]; attack surface, related to the entry and exit points via which attacks can be performed [25]; interdependency, related to the relationship of the IoT system with other IT/OT/IoT systems that could increase the severity of the attack [26]; scalability, related to the coverage area that can be affected by the propagation of the attack [27]; severity, related to the value of the damage that can be caused by the attack [28]; susceptibility, related to the predisposition to pick up the effects of an attack [29]; type of attack, related to the attack vector, technique or methodology [30,31]; device type, related to the type of IoT device [32,33]; type of information, related to the type of information processed, stored, or transmitted by the device [34]; uncertainty, related to the unknown factors that could affect the security of IoT systems [35]; vulnerabilities, related to the weak points that IoT systems may have and that may increase the possibility of being affected by an attack [36][37][38][39][40][41]. The density values of the codes (factors) are shown in Figure 4. From the quality analysis, we identified 11 factors of IoT devices that could affect that security risk value. ...
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Iot security for dummies
  • Lawrence Miller
Lawrence Miller. Iot security for dummies, carrie a. johnson, ed, 2016.