CRJun 5, 2017

A Privacy-preserving Community-based P2P OSNs Using Broadcast Encryption Supporting Recommendation Mechanism

arXiv:1706.01324v11 citations
Originality Incremental advance
AI Analysis

This addresses privacy issues for users of online social networks, but it appears incremental as it combines existing techniques like broadcast encryption and reputation mechanisms in a new context.

The paper tackles the problem of security and privacy concerns in centralized online social networks by proposing a privacy-preserving peer-to-peer (P2P) scheme with a recommendation mechanism, resulting in a system that meets design goals with reduced overhead as demonstrated through security analysis and performance evaluation.

Online Social Networks (OSNs) have become one of the most important activities on the Internet, such as Facebook and Google+. However, security and privacy have become major concerns in existing C/S based OSNs. In this paper, we propose a novel scheme called a Privacy-preserving Community-based P2P OSNs Using Broadcast Encryption Supporting Recommendation Mechanism (PCBE) that supports cross-platform availability in stringent privacy requirements. For the first time, we introduce recommendation mechanism into a privacy-preserving P2P based OSNs, in which we firstly employ the Open Directory Project to generate user interest model. We firstly introduce broadcast encryption into P2P community-based social networks together with reputation mechanism to decrease the system overhead. We formulate the security requirements and design goals for privacy- preserving P2P based OSNs supporting recommendation mechanism. The RESTful web-services help to ensure cross-platform availability and transmission security. As a result, thorough security analysis and performance evaluation on experiments demonstrate that the PCBE scheme indeed accords with our proposed design goals.

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