Defending against Contagious Attacks on a Network with Resource Reallocation

TL;DR

This paper studies a network defense model against contagious attacks, considering resource reallocation constraints, and provides computational complexity results, an optimization formulation, and an approximation algorithm with positive experimental outcomes.

Contribution

It introduces a novel resource reallocation model for contagious attacks, analyzes its computational hardness, and offers practical algorithms with proven effectiveness.

Findings

Computing optimal reallocation is NP-hard.

Optimal resource allocation without reallocation is NP-hard.

Proposed algorithms perform well in minimizing damage.

Abstract

In classic network security games, the defender distributes defending resources to the nodes of the network, and the attacker attacks a node, with the objective to maximize the damage caused. Existing models assume that the attack at node u causes damage only at u. However, in many real-world security scenarios, the attack at a node u spreads to the neighbors of u and can cause damage at multiple nodes, e.g., for the outbreak of a virus. In this paper, we consider the network defending problem against contagious attacks. Existing works that study shared resources assume that the resource allocated to a node can be shared or duplicated between neighboring nodes. However, in real world, sharing resource naturally leads to a decrease in defending power of the source node, especially when defending against contagious attacks. To this end, we study the model in which resources allocated to a node can only be transferred to its neighboring nodes, which we refer to as a reallocation process. We show that this more general model is difficult in two aspects: (1) even for a fixed allocation of resources, we show that computing the optimal reallocation is NP-hard; (2) for the case when reallocation is not allowed, we show that computing the optimal allocation (against contagious attack) is also NP-hard. For positive results, we give a mixed integer linear program formulation for the problem and a bi-criteria approximation algorithm. Our experimental results demonstrate that the allocation and reallocation strategies our algorithm computes perform well in terms of minimizing the damage due to contagious attacks.