Two-layer deception model based on signaling games against cyber attacks on cyber-physical systems
Two-layer deception model based on signaling games against cyber attacks on cyber-physical systems
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.
171559-171570
Kamdem, Priva Chassem
6ad7624b-ae01-43e6-8a91-e6178ae09f22
Zemkoho, Alain B.
30c79e30-9879-48bd-8d0b-e2fbbc01269e
Njilla, Laurent
e3080135-a677-4208-ada9-f1bc90a36118
Nkenlifack, Marcellin
4b90915c-3f06-4a5b-b4d1-818bb26a3eef
Kamhoua, Charles A.
192fa26f-70a6-4680-a2f4-f49047d2430b
11 October 2024
Kamdem, Priva Chassem
6ad7624b-ae01-43e6-8a91-e6178ae09f22
Zemkoho, Alain B.
30c79e30-9879-48bd-8d0b-e2fbbc01269e
Njilla, Laurent
e3080135-a677-4208-ada9-f1bc90a36118
Nkenlifack, Marcellin
4b90915c-3f06-4a5b-b4d1-818bb26a3eef
Kamhoua, Charles A.
192fa26f-70a6-4680-a2f4-f49047d2430b
Kamdem, Priva Chassem, Zemkoho, Alain B., Njilla, Laurent, Nkenlifack, Marcellin and Kamhoua, Charles A.
(2024)
Two-layer deception model based on signaling games against cyber attacks on cyber-physical systems.
IEEE Access, 12, .
(doi:10.1109/ACCESS.2024.3478808).
Abstract
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.
Text
Two-Layer_Deception_Model_Based_on_Signaling_Games_Against_Cyber_Attacks_on_Cyber-Physical_Systems
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More information
Accepted/In Press date: 5 October 2024
Published date: 11 October 2024
Identifiers
Local EPrints ID: 508577
URI: http://eprints.soton.ac.uk/id/eprint/508577
ISSN: 2169-3536
PURE UUID: 345cffc6-0bd6-4952-bfb8-3637879dc95c
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Date deposited: 27 Jan 2026 18:00
Last modified: 28 Jan 2026 03:37
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Contributors
Author:
Priva Chassem Kamdem
Author:
Laurent Njilla
Author:
Marcellin Nkenlifack
Author:
Charles A. Kamhoua
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