Information systems security : ... international conference, ICISS ... : proceedings. ICISS (Conference) (1st : 2005 : Kolkata, India)最新文献

英文中文

Privacy-Preserving Friend Recommendation in an Integrated Social Environment. 在综合社会环境中保护隐私的朋友推荐。

Information systems security : ... international conference, ICISS ... : proceedings. ICISS (Conference) (1st : 2005 : Kolkata, India)

Pub Date : 2020-12-01 Epub Date: 2020-12-06 DOI: 10.1007/978-3-030-65610-2_8

Nitish M Uplavikar, Jaideep Vaidya, Dan Lin, Wei Jiang

Ubiquitous Online Social Networks (OSN)s play a vital role in information creation, propagation and consumption. Given the recent multiplicity of OSNs with specially accumulated knowledge, integration partnerships are formed (without regard to privacy) to provide an enriched, integrated and personalized social experience. However, given the increasing privacy concerns and threats, it is important to develop methods that can provide collaborative capabilities while preserving user privacy. In this work, we focus on friend recommendation systems (FRS) for such partnered OSNs. We identify the various ways through which privacy leaks can occur, and propose a comprehensive solution that integrates both Differential Privacy and Secure Multi-Party Computation to provide a holistic privacy guarantee. We analyze the security of the proposed approach and evaluate the proposed solution with real data in terms of both utility and computational complexity.

无处不在的在线社交网络(OSN)在信息的创造、传播和消费中发挥着至关重要的作用。考虑到近年来osn的多样性和特殊知识的积累，形成了集成伙伴关系(不考虑隐私)，以提供丰富、集成和个性化的社交体验。然而，考虑到日益增加的隐私问题和威胁，开发能够在保护用户隐私的同时提供协作功能的方法非常重要。在这项工作中，我们专注于这种合作osn的朋友推荐系统(FRS)。我们确定了可能发生隐私泄露的各种途径，并提出了一个综合的解决方案，将差分隐私和安全多方计算相结合，提供全面的隐私保障。我们分析了所提出方法的安全性，并用实际数据从效用和计算复杂度两方面对所提出的解决方案进行了评估。

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