Proactive Trust Classification for Detection of Replication
Attacks in 6LoWPAN-based IoT

J 2021

Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT

MBAREK, Bacem; Mouzhi GE and Tomáš PITNER

Basic information

Original name

Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT

Authors

MBAREK, Bacem (788 Tunisia, belonging to the institution); Mouzhi GE (156 China) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

Internet of Things; Engineering Cyber Physical Human Systems, ELSEVIER, 2021, 2543-1536

Other information

Language

English

Type of outcome

Article in a journal

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Netherlands

Confidentiality degree

is not subject to a state or trade secret

References:

ScienceDirect

Impact factor

Impact factor: 5.711

RIV identification code

RIV/00216224:14330/21:00122050

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1016/j.iot.2021.100442

UT WoS

000723420400014

EID Scopus

2-s2.0-85115010510

Keywords in English

Internet of Things; Detection strategy; Trust in IoT; Replication attack; 6LoWPAN

Abstract

V originále

The 6LoWPAN standard has been widely applied in different Internet of Things (IoT) application domains. However, since the nodes in the IoT are mostly resource constrained, 6LoWPAN is vulnerable to a variety of security attacks. Among others, replication attack is one of the severe security threads to IoT networks. This paper therefore proposes a trust-based detection strategy against replication attacks in IoT, where a number of replica nodes are intentionally inserted into the network to test the reliability and response of witness nodes. We further assess the feasibility of the proposed detection strategy and compare with two other strategies such as brute-force and first visited strategy via a thorough simulation. The evaluation takes into account the detection probability for compromised attacks, the execution time of transactions and rate of communication failure. The simulation results show that while maintaining detection runtime on average 60 s for up to 1000 nodes, the proposed trust-based strategy can significantly increase the detection probability to 90% on average against replication attacks and in turn significantly reduce the communication failure.

Cite

MBAREK, Bacem; Mouzhi GE and Tomáš PITNER. Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT. Internet of Things; Engineering Cyber Physical Human Systems. ELSEVIER, 2021, vol. 16, No 1, p. 1-8. ISSN 2543-1536. Available from: https://dx.doi.org/10.1016/j.iot.2021.100442.

@article{1785257,
   author = {Mbarek, Bacem and Ge, Mouzhi and Pitner, Tomáš},
   article_number = {1},
   doi = {http://dx.doi.org/10.1016/j.iot.2021.100442},
   keywords = {Internet of Things; Detection strategy; Trust in IoT; Replication attack; 6LoWPAN},
   language = {eng},
   issn = {2543-1536},
   journal = {Internet of Things; Engineering Cyber Physical Human Systems},
   title = {Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT},
   url = {https://www.sciencedirect.com/science/article/pii/S2542660521000858},
   volume = {16},
   year = {2021}
}

TY  - JOUR
ID  - 1785257
AU  - Mbarek, Bacem - Ge, Mouzhi - Pitner, Tomáš
PY  - 2021
TI  - Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT
JF  - Internet of Things; Engineering Cyber Physical Human Systems
VL  - 16
IS  - 1
SP  - 1-8
EP  - 1-8
PB  - ELSEVIER
SN  - 25431536
KW  - Internet of Things
KW  - Detection strategy
KW  - Trust in IoT
KW  - Replication attack
KW  - 6LoWPAN
UR  - https://www.sciencedirect.com/science/article/pii/S2542660521000858
N2  - The 6LoWPAN standard has been widely applied in different Internet of Things (IoT) application domains. However, since the nodes in the IoT are mostly resource constrained, 6LoWPAN is vulnerable to a variety of security attacks. Among others, replication attack is one of the severe security threads to IoT networks. This paper therefore proposes a trust-based detection strategy against replication attacks in IoT, where a number of replica nodes are intentionally inserted into the network to test the reliability and response of witness nodes. We further assess the feasibility of the proposed detection strategy and compare with two other strategies such as brute-force and first visited strategy via a thorough simulation. The evaluation takes into account the detection probability for compromised attacks, the execution time of transactions and rate of communication failure. The simulation results show that while maintaining detection runtime on average 60 s for up to 1000 nodes, the proposed trust-based strategy can significantly increase the detection probability to 90% on average against replication attacks and in turn significantly reduce the communication failure.
ER  -

MBAREK, Bacem; Mouzhi GE and Tomáš PITNER. Proactive Trust Classification for Detection of Replication Attacks in 6LoWPAN-based IoT. \textit{Internet of Things; Engineering Cyber Physical Human Systems}. ELSEVIER, 2021, vol.~16, No~1, p.~1-8. ISSN~2543-1536. Available from: https://dx.doi.org/10.1016/j.iot.2021.100442.

Přehled o publikaci