Reputation attacks detection for effective trust assessment among cloud services

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013
Pages469-476
Number of pages8
DOIs
StatePublished - 2013
Externally publishedYes
Event12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013 - Melbourne, VIC, Australia
Duration: 16 Jul 201318 Jul 2013

Publication series

NameProceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013

Conference

Conference12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period16/07/1318/07/13

Keywords

  • attacks detection
  • cloud computing
  • credentials
  • credibility
  • privacy
  • reputation
  • Trust management

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