Name
Abstract | ||
|---|---|---|
De-anonymizing social networks has become a direct threat to people'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 networks. 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 Erdös - Rényi model(ER model). We also validated our results on both synthetic and real data.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3321408.3321577 | Proceedings of the ACM Turing Celebration Conference - China |
Keywords | Field | DocType |
de-anonymization, graphing matching, partial overlap | Social network,Computer science,Theoretical computer science | Conference |
ISBN | Citations | PageRank |
978-1-4503-7158-2 | 1 | 0.36 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongzhao Hu | 1 | 5 | 1.80 |
| Luoyi Fu | 2 | 415 | 58.53 |
| Xiaoying Gan | 3 | 344 | 48.16 |