社交网络中的社团隐私研究综述

doi:10.11959/j.issn.2096-109x.2021021

Abstract

Abstract:

Community is an important feature of social network and the development of community detection technology brings the danger of privacy disclosure to network users.How to protect sensitive community information from being leaked and ensure the security of users and communities has become a research hotspot in the field of network security.In recent years, community privacy protection technology has made initial progress, but there is a few survey on the research of community privacy or community security in social networks, and it may limit the potential and long-term development of this research topic.The research on the privacy of community structure was mainly reviewed and the related works on community security were classified, summarized, compared.The hot issues of community security in the future were proposed.

Key words: social network, community detection, community privacy, community safety, community hiding

CLC Number:

TP309

Zhongyuan JIANG, Xianyu CHEN, Jianfeng MA. Survey of community privacy in social network[J]. Chinese Journal of Network and Information Security, 2021, 7(2): 10-21.

Figures/Tables 7

文献	操作	技术	不足之处
文献[27]	增边或删边	K-同构、 $K_{-}^{+}$ 同构	节点角色不足、算法优化
文献[28]	匿名化	分级隐私保护	等级划分依据单一、薄弱

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社交网络	节点数目	边数目	描述
kar	34	78	Zachary Karate's Club
dol	62	159	Dolphins association
mad	62	159	Madrid Train Bombing
lesm	77	154	Co-appearances of characters in Les Miserables
polb	105	441	Books about US politics
words	112	425	Adjectives/nouns in the novel David Copperfield
nets	1 589	5 486	Net Theory co-authors
erdos	6 100	9 939	Erdos collaborations
faceb	6 387	2.17×10⁵	Facebook
pow	4 941	6 594	USA Power Grid
astr	1.79×10⁴	1.97×10⁵	Astrophysics co-authors
4sq	6.39×10⁵	3.2×10⁶	Foursquare
dblp	5.405×10⁵	1.52×10⁷	DBLP
amz	5.48×10⁵	9.25×10⁵	Amazon metadata
you	1×10⁶	3×10⁶	Youtube dataset
ork	3×10⁶	1.172×10⁸	Orkut social network

文献	操作	技术	所需网络知识	不足之处
文献[22]	增边、删边	安全性、模块度	目标社团节点的边	检测单一、反欺骗问题
文献[23]	增边、删边	新的安全性	目标社团节点的边	检测单一、真实应用
文献[24]	增边、删边	模块度	目标社团节点的边	研究知识不足、有局限性
文献[25]	增边	模块度	节点中心性	网络规模小、关注点单一
文献[26]	增边、删边	模块度、遗传算法	目标社团节点的边	检测单一、单目标优化

Survey of community privacy in social network

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