Visible to the public Improved trustworthiness judgment in open networks

TitleImproved trustworthiness judgment in open networks
Publication TypeConference Paper
Year of Publication2017
AuthorsYou, J., Shangguan, J., Sun, Y., Wang, Y.
Conference Name2017 International Smart Cities Conference (ISC2)
Date Publishedsep
ISBN Number978-1-5386-2524-8
KeywordsCollaboration, Collaborative recommendation, collaborative recommendation mechanism, composability, Computational modeling, cyber physical systems, decision making, interactive success rate, open networks, open systems, Peer-to-peer computing, pubcrawl, recommender systems, reliability, Resiliency, security of data, Software, statistical analysis, statistical trust value, trust data, trust model, Trusted Computing, trustworthiness judgment, Trustworthy Systems, Uncertainty, uncertainty analysis, Wireless sensor networks

The collaborative recommendation mechanism is beneficial for the subject in an open network to find efficiently enough referrers who directly interacted with the object and obtain their trust data. The uncertainty analysis to the collected trust data selects the reliable trust data of trustworthy referrers, and then calculates the statistical trust value on certain reliability for any object. After that the subject can judge its trustworthiness and further make a decision about interaction based on the given threshold. The feasibility of this method is verified by three experiments which are designed to validate the model's ability to fight against malicious service, the exaggeration and slander attack. The interactive success rate is significantly improved by using the new model, and the malicious entities are distinguished more effectively than the comparative model.

Citation Keyyou_improved_2017