稳健性(进化)
计算机科学
膨胀的
数据科学
网络拓扑
复杂网络
数据挖掘
万维网
计算机网络
抗压强度
生物化学
基因
复合材料
化学
材料科学
作者
Scott Freitas,Diyi Yang,Srijan Kumar,Hanghang Tong,Duen Horng Chau
出处
期刊:IEEE Transactions on Knowledge and Data Engineering
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:: 1-1
被引量:26
标识
DOI:10.1109/tkde.2022.3163672
摘要
The study of network robustness is a critical tool in the characterization and sense making of complex interconnected systems such as infrastructure, communication and social networks. While significant research has been conducted in these areas, gaps in the surveying literature still exist. Answers to key questions are currently scattered across multiple scientific fields and numerous papers. In this survey, we distill key findings across numerous domains and provide researchers crucial access to important information by(1) summarizing and comparing recent and classical graph robustness measures; (2) exploring which robustness measures are most applicable to different categories of networks (e.g., social, infrastructure); (3) reviewing common network attack strategies, and summarizing which attacks are most effective across different network topologies; and (4) extensive discussion on selecting defense techniques to mitigate attacks across a variety of networks. This survey guides researchers and practitioners in navigating the expansive field of network robustness, while summarizing answers to key questions. We conclude by highlighting current research directions and open problems.
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