A Novel Sybil Attack Detection Mechanism for Mobile IoT Networks

被引:1
作者
Dogan-Tusha, Seda [1 ]
Althunibat, Saud [2 ]
Qaraqe, Marwa [1 ]
机构
[1] Hamad Bin Khalifa Univ, Qatar Fdn, Div Informat & Comp Technol, Coll Sci & Engn, Doha, Qatar
[2] Al Hussein Bin Talal Univ, Dept Commun Engn, Maan, Jordan
来源
2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022) | 2022年
关键词
Doppler effect; illegitimate nodes; mobility; IoT networks; OFDM transmission; security; Sybil attack; WIRELESS SENSOR NETWORKS; CFO ESTIMATION;
D O I
10.1109/GLOBECOM48099.2022.10000934
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
IoT (Internet of Things) networks are becoming an integral part of everyday life. The exponential growth in these networks poses various privacy and security threats for the users and the vendors. Among these threats are Sybil attacks, which occurs due to poor authentication capabilities and thus a malicious node gets access to any information on the host. The malicious node uses its' fake identities to impersonate legitimate nodes and transmit misleading data to the central entity. However, conventional cryptographical approaches are not always suitable for IoT nodes due to the their limited resources. Therefore, physical layer security (PLS) solutions become more and more important for IoT networks. In this regard, this study introduces a novel technique for detecting Sybil attacks in mobile networks, which stands in contrast to the current methods developed for stationary environment, i.e., time-invariant channel. Specifically, this work exploits the Doppler shift caused by the mobility in the environment to identify Sybil nodes in the network. If the nodes belong to the same terminal, they experience the same amount of Doppler shift. The detection performance of the proposed scheme has been evaluated under different system configurations. The obtained results show that the performance of the proposed scheme improves as the amount of Doppler shift increases.
引用
收藏
页码:1838 / 1843
页数:6
相关论文
共 23 条
[1]   Signal Strength Based Sybil Attack Detection in Wireless Ad hoc Networks [J].
Abbas, S. ;
Merabti, M. ;
Llewellyn-Jones, D. .
2009 SECOND INTERNATIONAL CONFERENCE ON DEVELOPMENTS IN ESYSTEMS ENGINEERING (DESE 2009), 2009, :190-195
[2]  
[Anonymous], 2010, PROC IEEE GLOBAL TEL
[3]   Security of the Internet of Things: Vulnerabilities, Attacks, and Countermeasures [J].
Butun, Ismail ;
Osterberg, Patrik ;
Song, Houbing .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2020, 22 (01) :616-644
[4]   A Survey on Technologies, Standards and Open Challenges in Satellite IoT [J].
Centenaro, Marco ;
Costa, Cristina E. ;
Granelli, Fabrizio ;
Sacchi, Claudio ;
Vangelista, Lorenzo .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2021, 23 (03) :1693-1720
[5]  
Demirbas Murat., 2006, IEEE, P1
[6]  
Gao FF, 2006, IEEE ICC, P1421
[7]   Training Design for Repetitive-Slot-Based CFO Estimation in OFDM [J].
Ghogho, Mounir ;
Ciblat, Philippe ;
Swami, Ananthram ;
Bianchi, Pascal .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (12) :4958-4964
[8]   Classifications and Applications of Physical Layer Security Techniques for Confidentiality: A Comprehensive Survey [J].
Hamamreh, Jehad M. ;
Furqan, Haji M. ;
Arslan, Huseyin .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (02) :1773-1828
[9]   A Novel Model of Sybil Attack in Cluster-Based Wireless Sensor Networks and Propose a Distributed Algorithm to Defend It [J].
Jamshidi, Mojtaba ;
Zangeneh, Ehsan ;
Esnaashari, Mehdi ;
Darwesh, Aso Mohammad ;
Meybodi, Mohammad Reza .
WIRELESS PERSONAL COMMUNICATIONS, 2019, 105 (01) :145-173
[10]  
Jan MA, 2015, 2015 IEEE TRUSTCOM/BIGDATASE/ISPA, VOL 1, P318, DOI [10.1109/Trustcom-2015.390, 10.1109/Trustcom.2015.390]