Abstract
AbstractUser alignment across online social network platforms (OSNPs) is a growing concern with the rapid development of internet technology. In reality, users tend to register different accounts on multiple OSNPs, and the network platforms are reluctant to share network structure and user’s information due to business interest and privacy protection, which brings great obstacles to cross-platform user alignment. In view of this, we propose a homomorphic encryption-based social network alignment (HE-SNA) algorithm from the perspective of privacy leakage. Specifically, we first consider the OSNPs as a system containing multiple social networks, that each participant of OSNPs owns part of the network, i.e., a separate private sub-network. Then, encryption, fusion and decryption operations of the alignment information are performed by two third-party servers using HE scheme, which can protect the privacy information of sub-networks effectively. Finally, each sub-network uses the fused alignment information sent back from the third-party server for user alignment. Experimental results show that the HE-SNA method can provide a sum of locally trained models to third-party servers without leaking the privacy of any single sub-network. Moreover, the HE-SNA achieves a promising network alignment performance than only using the structural information and alignment data of single private sub-network while protecting its topology structure information.
Funder
Anhui Provincial Natural Science Foundation
Key Projects of Natural Science Research of Universities in Anhui Province
University Synergy Innovation Program of Anhui Province
MOE (Ministry of Education in China) Youth Foundation Project of Humanities and Social Sciences
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence
Cited by
1 articles.
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