Affiliation:
1. Xidian University 8 Aalto University
2. Xidian University
3. St. Francis Xavier University
Abstract
Pervasive Social Networking (PSN) supports online and instant social activities with the support of heterogeneous networks. Since reciprocal activities among both familiar/unfamiliar strangers and acquaintances are quite common in PSN, it is essential to offer trust information to PSN users. Past work normally evaluates trust based on a centralized party, which is not feasible due to the dynamic changes of PSN topology and its specific characteristics. The literature still lacks a decentralized trust evaluation scheme in PSN. In this article, we propose a novel blockchain-based decentralized system for trust evaluation in PSN, called Social-Chain. Considering mobile devices normally lack computing resources to process cryptographic puzzle calculation, we design a lightweight consensus mechanism based on Proof-of-Trust (PoT), which remarkably improves system effectivity compared with other blockchain systems. Serious security analysis and experimental results further illustrate the security and efficiency of Social-Chain for being feasibly applied into PSN.
Funder
the Academy of Finland
NSFC
the Key Lab of Information Network Security, Ministry of Public Security
open grant of the Tactical Data Link Lab of the 20th Research Institute of China Electronics Technology Group Corporation, P.R. China
the Shaanxi Innovation Team project
the National Postdoctoral Program for Innovative Talents
the Project funded by China Postdoctoral Science Foundation
the 111 project
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
Reference54 articles.
1. 2017. Qtum whitepaper. Retrieved from https://whitepaperdatabase.com/qtum-whitepaper/. 2017. Qtum whitepaper. Retrieved from https://whitepaperdatabase.com/qtum-whitepaper/.
2. 2016. Waves whitepaper. Retrieved from https://blog.wavesplatform.com/waves-whitepaper-164dd6ca6a23. 2016. Waves whitepaper. Retrieved from https://blog.wavesplatform.com/waves-whitepaper-164dd6ca6a23.
3. Ouroboros Genesis
4. Detecting Sybil attacks using proofs of work and location in vanets;Baza Mohamed;IEEE Trans. Depend. Sec. Comput. arXiv,2019
Cited by
41 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献