移动智能终端正在成为人们日常生活的核心通信设备,参与式感知的隐私保护技术已成为研究热点.研究和解决数据以及位置隐私保护问题对参与式感知的大规模安全使用具有重要意义,然而参与式感知的特征使得隐私保护技术面临诸多挑战.该文对参与式感知隐私保护现有的研究成果进行了综述,首先介绍了参与式感知的基本应用和攻击模型,然后按照基于分组统计、第三方验证、K-匿名、数字加密4种策略对现有成果进行了分类,阐述了代表性的隐私保护技术,接着分析和比较了各技术的性能并总结了各技术的主要优缺点,最后提出了未来的研究方向.
Participatory sensing (PS) is an emerging area of interest for researchers as mobile intelligent terminals are becoming the core communication device in people's everyday lives. Privacy preservation techniques in PS have attracted more and more attentions. Researching and solving the problems of data privacy preservation along with location privacy preservation is essential to widespread employment of PS. However, inherent characteristics of PS make privacy preservation face series of challenging problems. This paper surveys the state-of-the-art privacy preservation techniques in PS. First, this paper reviews the basic applications and attack models. Second, existing works are classified into four categories, including packet statistics, third-party verification, K-anonymous and digital encryption. Then this paper describes the key techniques of privacy preservation in PS, analyzes and compares the performance of these techniques, and summarizes the main advantages and disadvantages of these techniques. Finally, suggestions for future research works are put forward. Packet statistics are used when participants upload data. First, the data are cut into a number of packets or chosen from n packets data. Then the data packets are distributed to neighboring nodes. After that the sink or the qureier completes information reorganization and integrity verification. Packet statistics are always used along with random walker, delayed transmitting, hop-by-hop eneryption and data perturbation. In order to protect the participant privacy in the case of an untrusted server, one of the present methods is to add Trusted Third-Party (TTP) between participants and server. Participants upload data or the server assigns tasks all needs to go through TTP verification. Because the server cannot contact with participants' sensitive information directly, so as to effectively prevent the correlation attack and other attacks with background knowledge. Special network coding techniques are often needed when a TTP is used for v