NDLI: Toward trustworthy social network services: A robust design of recommender systems

Content Provider	IEEE Xplore Digital Library
Author	Giseop Noh Hayoung Oh Kyu-haeng Lee Chong-kwon Kim
Copyright Year	2011
Abstract	In recent years, electronic commerce and online social networks (OSNs) have experienced fast growth, and as a result, recommendation systems (RSs) have become extremely common. Accuracy and robustness are important performance indexes that characterize customized information or suggestions provided by RSs. However, nefarious users may be present, and they can distort information within the RSs by creating fake identities (Sybils). Although prior research has attempted to mitigate the negative impact of Sybils, the presence of these fake identities remains an unsolved problem. In this paper, we introduce a new weighted link analysis and influence level for RSs resistant to Sybil attacks. Our approach is validated through simulations of a broad range of attacks, and it is found to outperform other state-of-the-art recommendation methods in terms of both accuracy and robustness.
Starting Page	145
Ending Page	156
Page Count	12
File Size	1271747
File Format	PDF
ISSN	12292370
Volume Number	17
Issue Number	2
Language	English
Publisher	Editorial Department of Journal of Communications and Networks
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	JCN
Subject Keyword	Social network services Robustness Bipartite graph Accuracy Algorithm design and analysis Recommender systems Principal component analysis Sybil attack Link analysis recommender systems robust algorithm
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems

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