A privacy-preserved probabilistic routing index model for decentralised online social networks
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AbstractDespite the tremendous success of online social networks (OSNs), centrally controlled OSNs have inherent issues related to lack of user privacy and single point of failure. These limitations have motivated the research community to shift the computing paradigm from a centralised architecture to decentralised alternatives. Existing research works mainly focused on the routing mechanisms using social information in decentralised OSNs, without considering the user's privacy. This paper proposes a self-organised decentralised architecture (SDA) that leverages privacy-preserved routing methods to facilitate query routing in decentralised social networks. This architecture encompasses a hash-based profiling model to characterise semantic features of the user's content with low dimensionality and privacy-aware mechanisms to organise similarity users into semantic communities. Furthermore, a probabilistic routing method is proposed to support efficient information dissemination and service discovery. The correctness and efficiency of our proposed approach are evaluated through simulations on real-world datasets. The experimental results demonstrated that our approach achieved a better topological structure with high routing efficiency.
CitationYuan, B., Gu, J. and Liu, L., (2019). ‘A Privacy-Preserved Probabilistic Routing Index Model for Decentralised Online Social Networks’. IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation Conference, Leicester, 19-23 Aug. New York: IEEE, pp. 1711-1716.
JournalProceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
TypeMeetings and Proceedings
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