De-anonymize Social Network Under Partial Overlap
De-anonymizing social networks has become a direct threat to peo-ple's privacy.Actually,It can be boiled down to graph matching problems.The attackers steal users'real information in anonymized social networks by mapping them to secondary cross-domain net-works.In particular,when partial node identity in the anonymized network is known,such attacks will become more powerful.Some scholars have studied seeded network de-anonymization.However,there is a lack of consideration for network overlap.We further expand the work of predecessors and consider partially overlapping networks de-anonymization with the aid of seeded nodes.We give a more general form of theoretical results under Erd?s-Rényi model(ER model).We also validated our results on both synthetic and real data.
De-anonymization Graphing Matching Partial Overlap
Zhongzhao Hu Luoyi Fu Xiaoying Gan
Dept.of Electronic Engineering Shanghai Jiao Tong University Shanghai,China Dept.of Computer Science Shanghai Jiao Tong University Shanghai,China
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
415-419
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）