A Rapid Source Localization Method in the Early Stage of Large-scale Network Propagation

Zhen Wang, Dongpeng Hou, Chao Gao, Jiajin Huang, Qi Xuan

科研成果: 书/报告/会议事项章节会议稿件同行评审

63 引用 (Scopus)

摘要

Recently, the rapid diffusion of malicious information in online social networks causes great harm to our society. Therefore, it is of great significance to localize diffusion sources as early as possible to stem the spread of malicious information. This paper proposes a novel sensor-based method, called greedy full-order neighbor localization (denoted as GFNL), to solve this problem under a low infection propagation in line with the real world. More specifically, GFNL includes two main components, i.e., the greedy-based sensor deployment strategy (DS) and direction-path-based source estimation strategy (ES). In more detail, to ensure sensors can observe a propagation information as early as possible, a set of sensors is deployed in a network to minimize the geodesic distance (i.e., the distance of the shortest path) between the candidate set and the sensor set based on DS. Then when a fraction of sensors observe a propagation, ES infers the source based on the idea that the distance of the actual propagation path is proportional to the observed time. Compared with some state-of-the-art methods, comprehensive experiments have proved the superiority and robustness of our proposed GFNL.

源语言英语
主期刊名WWW 2022 - Proceedings of the ACM Web Conference 2022
出版商Association for Computing Machinery, Inc
1372-1380
页数9
ISBN(电子版)9781450390965
DOI
出版状态已出版 - 25 4月 2022
活动31st ACM World Wide Web Conference, WWW 2022 - Virtual, Online, 法国
期限: 25 4月 202229 4月 2022

出版系列

姓名WWW 2022 - Proceedings of the ACM Web Conference 2022

会议

会议31st ACM World Wide Web Conference, WWW 2022
国家/地区法国
Virtual, Online
时期25/04/2229/04/22

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