论文标题
使用SIS模型在大型网络中的最佳网络安全投资：算法设计
Optimal Cybersecurity Investments in Large Networks Using SIS Model: Algorithm Design
论文作者
论文摘要
我们研究了大型网络/系统中（时间）平均安全成本的问题，包括许多相互依存的子系统，其中状态进化是由易感感染感染的（SIS）模型捕获的。安全成本反映了成功攻击后的感染和失败的安全投资，经济损失和恢复成本。我们表明，由此产生的优化问题是非凸的，并提出了一组算法 - 两个基于凸弛豫的算法，而其他两个用于查找局部最小化器的算法，基于降低的梯度方法和顺序凸面编程。同样，我们提供了一个足够的条件，在该条件下，凸松弛是精确的，因此它们的解决方案与原始问题的解决方案相吻合。提供数值结果以验证我们的分析结果并证明所提出的算法的有效性。
We study the problem of minimizing the (time) average security costs in large networks/systems comprising many interdependent subsystems, where the state evolution is captured by a susceptible-infected-susceptible (SIS) model. The security costs reflect security investments, economic losses and recovery costs from infections and failures following successful attacks. We show that the resulting optimization problem is nonconvex and propose a suite of algorithms - two based on a convex relaxation, and the other two for finding a local minimizer, based on a reduced gradient method and sequential convex programming. Also, we provide a sufficient condition under which the convex relaxations are exact and, hence, their solution coincides with that of the original problem. Numerical results are provided to validate our analytical results and to demonstrate the effectiveness of the proposed algorithms.
