Optimal Strategy for Cyberspace Mimic Defense Based on Game Theory

Abstract

Traditional defensive techniques are usually static and passive, and appear weak to confront highly adaptive and stealthy attacks. As a novel security theory, Cyberspace Mimic Defense (CMD) creates asymmetric uncertainty that favors the defender. CMD constructs multiple executors which are diverse functional equivalent variants for the protected target and arbitral mechanism. In this way, CMD senses the results of current running executors and changes the attack surface. Although CMD enhances the security of systems, there are still some critical gaps with respect to design a defensive strategy under costs and security. In this paper, we propose a dual model to dynamically select the number of executors being reconfigured according to the states of the executors. First, we establish a Markov anti-attack model to compare the effects of CMD under different types of attack. Then, we use a dynamic game of incomplete information to determine the optimal strategy, which achieves the balance of the number of reconfiguration and security. Finally, experimental results show that our dual model reduces defensive costs while guarantees security.

An Optimal Seed Scheduling Strategy Algorithm Applied to Cyberspace Mimic Defense

“…They evaluated the historical confidence of the executors by setting a sliding window, which can effectively improve the operating efficiency of the algorithm and the security of the system under non-uniform distributed cyber attacks. Moreover, by introducing dynamic game theory into the scheduling strategy, Zequan Chen et al [43] proposed a strategy that can balance the defense costs and system security. In this strategy, the number of executors will be dynamically adjusted according to the historical strategies of the attackers, which can reduce the defense cost of the system.…”

Attack–Defense Confrontation Analysis and Optimal Defense Strategy Selection Using Hybrid Game Theoretic Methods

“…Relying on the ability to make multifaceted decisions on power grid security issues, game theory is widely applied in the field of network security [9][10][11][12][13][14][15][16]. In [9], a security resource allocation game model is established to discuss the load redistribution attacks problem.…”

“…However, the model lacks in describing the cumulative profits in a dynamic, changing game process; ref. [13] establishes a Markov anti-attack model, compares the effectiveness of network space simulation defense under different attack types, and uses dynamic games with incomplete information to determine the optimal strategy; ref. [14] formulates a multistage optimization model for the deployment of a mobile target defense mechanism under a Markov decision, maximizing the profits under environmental constraints.…”

“…[14] formulates a multistage optimization model for the deployment of a mobile target defense mechanism under a Markov decision, maximizing the profits under environmental constraints. However, each iteration solution of [13,14] depends on the revenue in the current unit time, ignoring the previous revenue, bringing in an exponential increase in complex calculations; in [15], a Markovian-Stackelberg game is proposed to simulate the sequential actions of attackers and defenders, and a secure constrained optimal power flow is given, which preserves the safety margin of key components to minimize the power outage scale and potential future risks; in [16], the adversarial interaction of the attacker and defender is modeled as a resource-constrained game, and a linear-time algorithm is used to obtain the optimal defense strategy. However, the game process in the above works assumes that both sides (attacker and defender) of the game are in pure rationality.…”