Two-Layer Deception Model Based on Signaling Games Against Cyber Attacks on Cyber-Physical Systems

被引:0
|
作者
Kamdem, Priva Chassem [1 ]
Zemkoho, Alain B. [2 ]
Njilla, Laurent [3 ]
Nkenlifack, Marcellin [1 ]
Kamhoua, Charles A. [4 ]
机构
[1] Univ Dschang, Dept Math & Comp Sci, Dschang, Cameroon
[2] Univ Southampton, Sch Math Sci, Southampton SO17 1BJ, England
[3] Air Force Res Lab, Informat Assurance Branch, Rome, NY 13441 USA
[4] DEVCOM Army Res Lab, Charles Kamhoua Network Secur Branch, Adelphi, MD 20783 USA
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Games; Cyber-physical systems; Bayes methods; Physical layer; Hardware; Cyberattack; Uncertainty; Government; Adaptation models; Vehicle dynamics; cyberattacks; deception-based techniques; defender's action space; signaling games; perfect Bayesian Nash equilibrium;
D O I
10.1109/ACCESS.2024.3478808
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cyber-physical systems (CPS) are increasingly vulnerable to sophisticated cyber-attacks that can target multiple layers within the system. To strengthen defenses against these complex threats, deception-based techniques have emerged as a promising solution. While previous research has primarily focused on single-layer deception strategies, the authors argue that a multi-layer approach is essential for effectively countering advanced attackers capable of perceiving information across both the application and network layers. In this work, we propose a two-layer deception model based on signaling games to enhance the defense of CPS. Our model captures the dynamic, non-cooperative interactions between the attacker and defender under conditions of incomplete information. Unlike existing approaches, our model expands the defender's action space to incorporate deception at both the application and network layers, while maintaining the attacker's uncertainty about the true system type. Through analytical and simulation results, we identify the Perfect Bayesian Nash Equilibrium (PBNE) strategies for both players. Our findings demonstrate that the two-layer deception model significantly outperforms single-layer deception in deceiving the attacker and improving system resilience, particularly against sophisticated adversaries capable of perceiving information across multiple layers.
引用
收藏
页码:171559 / 171570
页数:12
相关论文
共 50 条
  • [21] Real-time detection of deception attacks in cyber-physical systems
    Feiyang Cai
    Xenofon Koutsoukos
    International Journal of Information Security, 2023, 22 : 1099 - 1114
  • [22] Optimal Stealthy Deception Attack Against Cyber-Physical Systems
    Zhang, Qirui
    Liu, Kun
    Xia, Yuanqing
    Ma, Aoyun
    IEEE TRANSACTIONS ON CYBERNETICS, 2020, 50 (09) : 3963 - 3972
  • [23] Cross level Detection of Sensor-based Deception Attacks on Cyber-Physical Systems
    Croteau, Brien
    Krishnankutty, Deepak
    Robucci, Ryan
    Patel, Chintan
    Banerjee, Nilanjan
    Kiriakidis, Kiriakos
    Severson, Tracie
    Rodriguez-Soda, Erick
    2017 IEEE 7TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER), 2017, : 1037 - 1042
  • [24] Optimal design and performance analysis of secure estimator for cyber-physical systems against deception attacks
    Han, Zhichen
    Zhang, Shengbing
    Jin, Zengwang
    Hu, Yanyan
    ASIAN JOURNAL OF CONTROL, 2024, 26 (05) : 2539 - 2552
  • [25] Secure state estimation for event-triggered cyber-physical systems against deception attacks
    Han, Zhichen
    Zhang, Shengbing
    Jin, Zengwang
    Hu, Yanyan
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2022, 359 (18): : 11155 - 11185
  • [26] Hybrid DeepGCL model for cyber-attacks detection on cyber-physical systems
    Rasim Alguliyev
    Yadigar Imamverdiyev
    Lyudmila Sukhostat
    Neural Computing and Applications, 2021, 33 : 10211 - 10226
  • [27] Hybrid DeepGCL model for cyber-attacks detection on cyber-physical systems
    Alguliyev, Rasim
    Imamverdiyev, Yadigar
    Sukhostat, Lyudmila
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (16): : 10211 - 10226
  • [28] Hybrid DeepGCL model for cyber-attacks detection on cyber-physical systems
    Alguliyev, Rasim
    Imamverdiyev, Yadigar
    Sukhostat, Lyudmila
    Neural Computing and Applications, 2021, 33 (16) : 10211 - 10226
  • [29] Integrity Attacks on Cyber-Physical Systems
    Mo, Yilin
    Sinopoli, Bruno
    HICONS 12: PROCEEDINGS OF THE 1ST ACM INTERNATIONAL CONFERENCE ON HIGH CONFIDENCE NETWORKED SYSTEMS, 2012, : 47 - 54
  • [30] Cryptanalytical Attacks on Cyber-physical Systems
    Novotny, Martin
    2016 5TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), 2016, : 10 - 10