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

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.

Cloud Data Management for Scientific Workflows: Research Issues, Methodologies, and State-of-the-Art

“…Furthermore, to reflect users' preferences on the datasets storage [55], we need to incorporate related parameters into the strategies which 1) guarantee all the application datasets' regenerations can fulfil users' tolerance of data accessing delay, and 2) allow users to store some datasets according to their preferences [56] [57].…”

A historical probability based noise generation strategy for privacy protection in cloud computing

“…We now perform an experimental simulation in our cloud computing simulation environment called SwinCloud [38]. Our aim is to simulate the random noise generation strategy and our HPNGS to demonstrate that our HPNGS can significantly reduce the number of noise requests.…”

“…K. Fukushima et al [36] discuss obfuscation mechanism in mobile condition. G. Zhang et al [37] discuss a trust mechanism in noise obfuscation scenarios in the cloud.…”

“…It is built on the computing facilities at Swinburne University of Technology [38]. In general, these functions of VMWare can offer unified computing and storage resources.…”

Extract reputable users for trust-aware applications

“…The users with higher reputation are usually regarded as more reliable. In the globalized trust-aware applications [3][4][5], the information given by the reliable users is usually regarded as more trustworthy. E.g., in the globalized trust-aware recommender system [6], items suggested by users with higher reputation will be recommended to users with priority.…”