A trust-based noise injection strategy for privacy protection in cloud

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A trust-based noise injection strategy for privacy protection in cloud

Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/219179

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Title: A trust-based noise injection strategy for privacy protection in cloud
Author(s): Zhang, Gaofeng; Yang, Yun; Yuan, Dong; Chen, Jinjun
Abstract: Cloud promises users that they can present and deploy IT services in a pay-as-you-go fashion in an open and virtualized cloud environment while saving huge capital investment in their own IT infrastructure. In this sense, protection of users' privacy is critical and has become one of the most concerned issues as otherwise users may eventually lose the confidence and passion of deploying cloud in practice. Under some special cloud circumstances, some users' privacy, such as plans or habits, could be induced from their service requests by service providers without permissions from users. In this regard, obfuscation strategy can protect this kind of privacy by injecting 'noise' service requests to confuse potential 'immoral' service providers. However, existing noise obfuscation strategies focus on single noise injection whereas investigation of noise injection architecture has been neglected. Especially, a common service pattern in inter-clouds environment, the cooperative service process including different service providers, makes the risk of privacy serious and uncontrollable by the spread of users' privacy. To address this, we present a novel trust-based noise injection strategy for privacy protection in cloud. To support the strategy, we describe our noise injection architecture in cloud which specializes in the relations between various service roles in inter-clouds based on our trust model. The simulation can demonstrate that our noise injection strategy could significantly improve the effectiveness of privacy protection.
Publication type: Journal article
Research centre: Swinburne University of Technology. Faculty of Information and Communication Technologies
Source: Software: Practice and Experience, Vol. 42, no. 4 (Apr 2012), pp. 431-445
Publication year: 2012
FOR Code(s): 08 Information and Computing Sciences; 17 Psychology and Cognitive Sciences
Keyword(s): Cloud computing; Noise injection strategy; Privacy protection; Trust
Publisher: John Wiley & Sons
ISSN: 0038-0644
Publisher URL: http://dx.doi.org/10.1002/spe.1052
Peer reviewed