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Community Deception in Large Networks: Through the Lens of Laplacian Spectrum

文献类型：期刊论文

作者Zhang, Chong3; Fu, Luoyi3; Ding, Jiaxin3; Cao, Xinde2; Long, Fei5; Wang, Xinbing3; Zhou, Lei1; Zhang, Jing1; Zhou, Chenghu4
刊名IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
出版日期2023-05-11
页码13
ISSN号2329-924X
关键词Laplace equations Image edge detection Eigenvalues and eigenfunctions Detection algorithms Perturbation methods Social networking (online) Lenses Community deception (CD) community detection Laplacian spectrum large network
DOI10.1109/TCSS.2023.3268564
通讯作者Wang, Xinbing(xwang8@sjtu.edu.cn)
英文摘要Many complex networks in the real world have community structures. Typical examples include online social net-works and ecology networks. While the identification of commu-nities bears numerous practical applications, with the increasing awareness of data security and privacy concerns, the need to protect the community affiliations of individuals from disclosing by attackers emerges. This raises the community deception (CD) problem, that is, the opposite of community detection, which asks for ways to minimally perturb the network structures by rewiring nodes so that the target communities maximally hide themself from community detection algorithms. To this end, we investigate the CD problem through a Laplacian spectrum lens and propose a method named ComDeceptor to hide a flexible target set of communities, which is more universal than most existing methods that either focus on hiding the entire communities or a single community. The key idea of ComDeceptor is to first allocate the resources of perturbations fairly and effectively. By proving that hiding communities through intercommunity edge addition and intracommunity edge deletion correspond to maximizing the second smallest eigenvalue ?(2) and minimizing the largest eigenvalue ?(n) of the graph Laplacian, respectively, ComDeceptor then incorporates efficient heuristics for approx-imately solving the problems, thus selecting the appropriate edge to perturb. Experimental results over nine real-world networks and six community detection algorithms not only demonstrate the efficiency of ComDeceptor, but also the superior performance on obfuscating community structures over the baselines.
WOS关键词COMPLEX NETWORKS ; ROBUSTNESS
资助项目NSF China[42050105] ; NSF China[62020106005] ; NSF China[62061146002] ; NSF China[61960206002] ; 100-Talents Program of Xinhua News Agency ; Shanghai Pilot Program for Basic Research through Shanghai Jiao Tong University ; Program of Shanghai Academic/Technology Research Leader[18XD1401800]
WOS研究方向Computer Science
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000988415500001
资助机构NSF China ; 100-Talents Program of Xinhua News Agency ; Shanghai Pilot Program for Basic Research through Shanghai Jiao Tong University ; Program of Shanghai Academic/Technology Research Leader
源URL[http://ir.igsnrr.ac.cn/handle/311030/197325]  
专题中国科学院地理科学与资源研究所
通讯作者Wang, Xinbing
作者单位1.Shanghai Jiao Tong Univ, Sch Oceanog, Shanghai 200240, Peoples R China
2.Shanghai Jiao Tong Univ, Sch Environm Sci & Engn, Shanghai 200240, Peoples R China
3.Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100864, Peoples R China
5.Xinhua News Agcy, State Key Lab Media Convergence Prod Technol & Sys, Beijing 100077, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Chong,Fu, Luoyi,Ding, Jiaxin,et al. Community Deception in Large Networks: Through the Lens of Laplacian Spectrum[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2023:13.
APA Zhang, Chong.,Fu, Luoyi.,Ding, Jiaxin.,Cao, Xinde.,Long, Fei.,...&Zhou, Chenghu.(2023).Community Deception in Large Networks: Through the Lens of Laplacian Spectrum.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,13.
MLA Zhang, Chong,et al."Community Deception in Large Networks: Through the Lens of Laplacian Spectrum".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2023):13.

入库方式： OAI收割

来源：地理科学与资源研究所

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