ArXiv TLDR

Zero-determinant Strategy for Moving Target Defense: Existence, Performance, and Computation

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2605.07854

Zhaoyang Cheng, Guanpu Chen, Yiguang Hong, Ming Cao, Mikael Skoglund

cs.GTcs.CR

TLDR

This paper proposes zero-determinant (ZD) strategies for Moving Target Defense (MTD) to achieve high performance with low computational cost.

Key contributions

  • Derives necessary and sufficient conditions for the existence of ZD strategies in MTD.
  • Shows ZD strategies can match the upper-bound performance of Stackelberg equilibrium (SSE).
  • Formulates programs and an algorithm to compute optimal ZD strategy parameters.
  • Demonstrates ZD strategies offer significantly lower computational complexity than SSE.

Why it matters

Moving Target Defense (MTD) is vital for security, but optimal strategies are often too complex. This paper introduces Zero-Determinant (ZD) strategies as a practical alternative. ZD strategies match the performance of optimal methods while significantly reducing computational cost, enabling broader deployment of MTD in real-world, multi-target systems.

Original Abstract

Moving Target Defense (MTD) is commonly formulated as a repeated security game to mitigate persistent threats. Although the strong Stackelberg equilibrium (SSE) characterizes the defender's optimal strategy in the leader-follower framework, computing the SSE often incurs high computational complexity, which significantly limits its practical deployment in MTD problems with multiple targets. This paper proposes adopting a zero-determinant (ZD) strategy for constructing an MTD strategy that achieves both high defensive performance and substantially low computational complexity. We first derive a necessary and sufficient condition for the existence of ZD strategies and investigate the performance of ZD strategies, which shows their upper-bound performance matches that of the SSE strategy. We then formulate two programs to find the optimal ZD strategy parameters under different conditions. Moreover, we design an algorithm to compute the proposed ZD strategies, along with the computational complexity analysis in comparison with the traditional SSE computation. Finally, we conduct experiments on two practical applications to verify our results.

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