Residential College | false |
Status | 已發表Published |
Defending against Contagious Attacks on a Network with Resource Reallocation | |
Rufan Bai1; Haoxing Lin1; Xinyu Yang1; Xiaowei Wu1; Minming Li2; Weijia Jia3 | |
2021-02-01 | |
Conference Name | 35th AAAI Conference on Artificial Intelligence, AAAI 2021 |
Source Publication | Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Press 2021, ISBN 978-1-57735-866-4 |
Volume | 6A |
Pages | 5135 - 5142 |
Conference Date | 02-09 02/2021 |
Conference Place | Virtual, Online |
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. |
Keyword | Network Defending Game Contagious Attack |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science ; Education & Educational Research |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Education, Scientific Disciplines |
WOS ID | WOS:000680423505027 |
The Source to Article | PB_Publication |
Scopus ID | 2-s2.0-85130073093 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) |
Corresponding Author | Xiaowei Wu |
Affiliation | 1.IoTSC, University of Macau 2.City University of Hong Kong 3.BNU (Zhuhai) & UIC |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Rufan Bai,Haoxing Lin,Xinyu Yang,et al. Defending against Contagious Attacks on a Network with Resource Reallocation[C], 2021, 5135 - 5142. |
APA | Rufan Bai., Haoxing Lin., Xinyu Yang., Xiaowei Wu., Minming Li., & Weijia Jia (2021). Defending against Contagious Attacks on a Network with Resource Reallocation. Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Press 2021, ISBN 978-1-57735-866-4, 6A, 5135 - 5142. |
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