Optimal cybersecurity investment with collaborative defense in scale-free supply chain networks: a stochastic game-based dynamic programming approach
研究了无标度供应链网络中风险通过数据连接直接和间接传播时的网络安全投资策略，提出了包含协作防御联盟的随机博弈框架，并用动态规划算法求解近似纳什均衡，发现协作防御不一定降低总成本。
We investigate cybersecurity investment strategies in scale-free supply chain networks where risk propagates directly and indirectly through data connections. A stochastic game framework is developed, incorporating a Gordon–Loeb direct attack function and multi-path cumulative indirect risk propagation. A collaborative defense coalition with joint investment pooling and shared liability is introduced to internalise externalities. An iterative best-response algorithm combined with dynamic programming is proposed to compute approximate Nash equilibria. Theoretical propositions characterise investment monotonicity, spillover effects, and the non-trivial impact of collaboration. Numerical experiments on a representative network reveal that collaborative defense does not always reduce total cost, especially when investment caps bind. The findings offer actionable insights for designing resilient cybersecurity strategies in interconnected supply chains.