Research On Group Privacy Protection Mechanism Based On Cloud Model

In recent years, a variety of privacy events emerge in endlessly, with privacy risk gradually increased, bringing huge losses for society, organizations and individuals. Especially with the popularity of cloud computing and various mobile applications, service providers have gathered more and more sensitive information. In this background, how to protect the privacy of our users is facing a serious challenge. As the privacy protection consciousness continuously strengthen, users should not only ensure the personal privacy protection of sensitive information, but also have further requirements on the user's group privacy showing the characteristics of the overall.The overall characteristics are showed by the group composed of individuals including sensitive information and need to be protected under certain circumstances. As time changes, under certain conditions, the trend of characteristics of the overall analyzed, may also sensitive information and also need to protect them. Therefore, we propose a privacy protection mechanism for group sensitive characteristics. We construct the distribution and trend change different but looks reasonable distribution and trend with original distribution and sensitive group characteristics change trend, using cloud model, based on the original distribution and sensitive group characteristics change trend, to a certain extent, hidden and confuse the true distribution and trend, so as to realize the sensitive group characteristics and change tendency of privacy protection, namely static and dynamic protection of privacy for groups.It shows that the group privacy protection mechanism proposed through analysis and experiment, can generate different but reasonable similar falsified data and distribution based on the real data using cloud model and can have the effect of confusion and protection. They have the good privacy protection effect to a great extent. With privacy protection awareness growing in today, group privacy will also have great application value.