Abstract
It is enormously challenging to achieve a satisfactory balance between quality of service (QoS) and users’ privacy protection along with measuring privacy disclosure in social Internet of Things (IoT). We propose a privacy-preserving personalized service framework (Persian) based on static Bayesian game to provide privacy protection according to users’ individual security requirements in social IoT. Our approach quantifies users’ individual privacy preferences and uses fuzzy uncertainty reasoning to classify users. These classification results facilitate trustworthy cloud service providers (CSPs) in providing users with corresponding levels of services. Furthermore, the CSP makes a strategic choice with the goal of maximizing reputation through playing a decision-making game with potential adversaries. Our approach uses Shannon information entropy to measure the degree of privacy disclosure according to the probability of game mixed strategy equilibrium. Experimental results show that Persian guarantees QoS and effectively protects user privacy despite the existence of adversaries.
Highlights
The rapid development of cloud computing and big data technologies has greatly promoted work productivity and life quality
In social Internet of Things (IoT), we mainly focus on how a cloud service providers (CSPs) provides personalized services for users
Users have to share their privacy to the CSP to exchange application privileges, so as to enjoy personalized services
Summary
The rapid development of cloud computing and big data technologies has greatly promoted work productivity and life quality. Zhang et al [27] attach importance to the social connection of users, consider the existence of untrusted service providers and malicious attackers, and propose and implement an effective IoT service with differential privacy protection. Considering big data privacy protection from the perspective of users’ interests and economics, the existing literatures [29] mainly describe the benefits and costs of participants by employing game theory, simulate the rational selection process, and formulate the optimal privacy protection scheme through Nash equilibrium [21]. In order to tackle this problem, this paper proposes the Persian framework, aiming at providing personalized services to social IoT users on the basis of protecting user privacy.
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