Details of Research Outputs

TitleDefending against Contagious Attacks on a Network with Resource Reallocation
Creator
Date Issued2021
Conference Name35th AAAI Conference on Artificial Intelligence, AAAI 2021
Source Publication35th AAAI Conference on Artificial Intelligence, AAAI 2021
Volume6A
Pages5135-5142
Conference DateFEB 02-09, 2021
Conference PlaceElectronic Network
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.

URLView source
Language英语English
Scopus ID2-s2.0-85130073093
Citation statistics
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/9364
CollectionFaculty of Science and Technology
Affiliation
1.IoTSC, University of Macau, Macao, China
2.City University of Hong Kong, Hong Kong, China
3.BNU (Zhuhai), UIC, China
Recommended Citation
GB/T 7714
Bai, Rufan,Lin, Haoxing,Yang, Xinyuet al. Defending against Contagious Attacks on a Network with Resource Reallocation[C], 2021: 5135-5142.
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