Wireless covert channel is an emerging covert communication technique which conceals the very existence of secret information in wireless signal including GSM, CDMA, and LTE. The secret message bits are always modulated into artificial noise superposed with cover signal, which is then demodulated with the shared codebook at the receiver. In this paper, we first extend the traditional KS test and regularity test in covert timing channel detection into wireless covert channel, which can be used to reveal the very existence of secret data in wireless covert channel from the aspect of multiorder statistics. In order to improve the undetectability, a wireless covert channel for OFDM-based communication system based on constellation shaping modulation is proposed, which generates additional constellation points around the standard points in normal constellations. The carrier signal is then modulated with the dirty constellation and the secret message bits are represented by the selection mode of the additional constellation points; shaping modulation is employed to keep the distribution of constellation errors unchanged. Experimental results show that the proposed wireless covert channel scheme can resist various statistical detections. The communication reliability under typical interference is also proved.
Cyber-physical system (CPS) is an advanced system that integrats physical processes, computation and communication resources. The security of cyber-physical systems has become an active research area in recent years. In this paper, we focus on defensive strategies against network attacks in CPS. We introduce both low-and highinteraction honeypots into CPS as a security management tool deliberately designed to be probed, attacked and compromised. In addition, an analysis resource constraint is introduced for the purpose of optimizing defensive strategies against network attacks in CPS. We study the offensive and defensive interactions of CPS and model the offensive and defensive process as an incomplete information game with the assumption that the defender's analysis resource is unknown to the attacker. We prove the existence of several Bayesian-Nash equilibria in the low-and high-interaction honeypot game without analysis cost constraints and obtain the attacker's equilibrium strategy firstly. Then, we take the impact of analysis cost on the capture effect of honeypots into consideration and further optimize the defensive strategy by allocating analysis resource between low-and high-interaction honeypot with resource constraint. Finally, the proposed method is evaluated through numerical simulation and prove to be effective in obtaining the optimal defensive strategy.
As one of the most critical infrastructure, the power grid has been increasingly threatened by network attacks, especially advanced persistent threats (APTs). APT in the power grid is a continual and stealthy attack that analyzes the interaction between the cyber layer and the physical layer. The existing offensive and defensive processes for power grid using honeypots against APTs are modeled based on full rationality. Therefore, both the attacker and the defender make decisions to maximize their payoffs under full rationality. However, fully rational decisions made by end-users are not always conformed with the real cases, and prospect theory is a typical boundedly rational method to model these deviations. In this study, we propose a subjective APT-honeypot game model to study the offensive and defensive interactions between the attacker and the defender based on the prospect theory. In this model, we protect the power grid bus nodes by deploying honeypots, which consider both low-and high-interaction honeypot modes. We prove the existence of Bayesian-Nash equilibrium strategies in defense and attack strategies under bounded rationality. In addition, we used IEEE-30 Bus system to verify the proposed model in this paper. Experiment results show that bounded rationality affects strategy selection and reduces attacker's payoffs. INDEX TERMS Honeypot, game theory, power grid, APT, prospect theory.
A cyber‐physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well‐funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game‐theoretical model considering both low‐ and high‐interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.
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