Distributed Detection with Multiple Sensors in the Presence of Sybil Attacks

被引:1
|
作者
Hashlamoun, Wael [1 ]
Brahma, Swastik [2 ]
Varshney, Pramod K. [3 ]
机构
[1] Birzeit Univ, Dept ECE, Birzeit, Palestine
[2] Univ Cincinnati, Dept CS, Cincinnati, OH 45221 USA
[3] Syracuse Univ, Dept EECS, Syracuse, NY 13244 USA
来源
2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022) | 2022年
关键词
Sensor Networks; Distributed Detection; Sybil Attack; Data Falsification; Game Theory; INFERENCE;
D O I
10.1109/GLOBECOM48099.2022.10001514
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers the problem of distributed detection in the presence of a Sybil attack where a malicious sensor node can send multiple falsified decisions using multiple fake identities to a Fusion Center (FC) to degrade its decision-making performance. We study the problem under the Neyman-Pearson (NP) setup. We find that, due to the Sybil attack, the decisions received at the FC become correlated and that the degree of correlation is dependent on the number of fake identities used. The paper characterizes the optimal Sybil attack that blinds the FC, i.e., makes the FC incapable of making an informed decision. We find that if the sum of the local detection and false alarm probabilities of the sensor nodes is 1, the FC can be made blind when at least 50% of the decisions are sent using fake identities. However, if this condition is not met, then all decisions would have to be sent using fake identities in order to blind the FC. The paper also investigates strategic interactions between the FC and the Sybil attacker using Game Theory and proves the existence of a Nash Equilibrium (NE). Numerical results are presented to gain important insights.
引用
收藏
页码:2770 / 2775
页数:6
相关论文
共 50 条
  • [1] Distributed Detection in the Presence of Byzantine Attacks
    Marano, Stefano
    Matta, Vincenzo
    Tong, Lang
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (01) : 16 - 29
  • [2] Overview of Sybil attacks and defenses in the distributed architecture
    Xu Z.
    Li X.
    Mao J.
    Liu J.
    Zhou Z.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2021, 48 (01): : 39 - 49
  • [3] A Trust Structure for Detection of Sybil Attacks in Opportunistic Networks
    Rashidibajgan, Samaneh
    2016 11TH INTERNATIONAL CONFERENCE FOR INTERNET TECHNOLOGY AND SECURED TRANSACTIONS (ICITST), 2016, : 347 - 351
  • [4] Distributed Bayesian Detection in the Presence of Byzantine Data
    Kailkhura, Bhavya
    Han, Yunghsiang S.
    Brahma, Swastik
    Varshney, Pramod K.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (19) : 5250 - 5263
  • [5] Distributed Detection Over Blockchain-Aided Internet of Things in the Presence of Attacks
    Jiang, Yiming
    Zhang, Jiangfan
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2023, 18 : 3445 - 3460
  • [6] Distributed inference in the presence of Byzantine sensors
    Marano, Stefano
    Matta, Vincenzo
    Tong, Lang
    2006 FORTIETH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-5, 2006, : 281 - +
  • [7] Resilient Consensus for Multi-Agent Systems in the Presence of Sybil Attacks
    Dong, Xiaochen
    Wu, Yiming
    Xu, Ming
    Zheng, Ning
    ELECTRONICS, 2022, 11 (05)
  • [8] Comparison of centralized and distributed CFAR detection with multiple sensors
    Guan, J
    Meng, XW
    He, Y
    Peng, YN
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2003, E86B (05) : 1715 - 1720
  • [9] A Regional Statistics Detection Scheme against Sybil Attacks in WSNs
    Li, Mingxi
    Xiong, Yan
    Wu, Xuangou
    Zhou, Xianchun
    Sun, Yuhui
    Chen, Shenpei
    Zhu, Xiaoya
    2013 12TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (TRUSTCOM 2013), 2013, : 285 - 291
  • [10] Distributed detection with fuzzy censoring sensors in the presence of noise uncertainty
    Mohammadi, A.
    Javadi, S. H.
    Ciuonzo, D.
    Persico, V
    Pescape, A.
    NEUROCOMPUTING, 2019, 351 : 196 - 204