Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/83851
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Type: Conference paper
Title: Reputation attacks detection for effective trust assessment among cloud services
Author: Noor, T.
Sheng, Q.
Alfazi, A.
Citation: Proceedings, 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013: pp.469-476
Publisher: IEEE
Publisher Place: United States
Issue Date: 2013
Series/Report no.: IEEE International Conference on Trust Security and Privacy in Computing and Communications
ISBN: 9780769550220
ISSN: 2324-898X
Conference Name: IEEE International Conference on Trust, Security and Privacy in Computing and Communications (12th : 2013 : Melbourne, Australia)
Statement of
Responsibility: 
Talal H. Noor, Quan Z. Sheng, and Abdullah Alfazi
Abstract: Consumers' feedback is a good source to help assess overall trustworthiness of cloud services. However, it is not unusual that a trust management system experiences malicious behaviors from its users (i.e., collusion or Sybil attacks). In this paper, we propose techniques for the detection of reputation attacks to allow consumers to effectively identify trustworthy cloud services. We introduce a credibility model that not only identifies misleading trust feedbacks from collusion attacks but also detects Sybil attacks, either strategic (in a long period of time) or occasional (in a short period of time). We have collected a large collection of consumer's trust feedbacks given on real-world cloud services (over 10, 000 records) to evaluate and demonstrate the applicability of our approach and show the capability of detecting such malicious behaviors.
Keywords: Trust management
cloud computing
credentials
credibility
reputation
attacks detection
privacy
Rights: © 2013 IEEE
DOI: 10.1109/TrustCom.2013.59
Appears in Collections:Aurora harvest
Computer Science publications

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