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Optimal Cybersecurity Investments in Large Networks Using SIS Model: Algorithm Design



Van Sy Mai, Richard La, Abdella Battou


We study the problem of minimizing the (time) average security costs in large 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.
IEEE/ACM Transactions on Networking


Cybersecurity investments, Optimization, SIS model


Mai, V. , La, R. and Battou, A. (2021), Optimal Cybersecurity Investments in Large Networks Using SIS Model: Algorithm Design, IEEE/ACM Transactions on Networking, [online],, (Accessed May 29, 2024)


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Created July 1, 2021, Updated February 23, 2022