Biblio

The unprecedented and enormous growth of cloud computing, especially online social networks, has resulted in numerous incidents of the loss of users' privacy. In this paper, we provide a framework, based on our anti-data-mining (ADM) principle, to enhance users' privacy against adversaries including: online social networks; search engines; financial terminal providers; ad networks; eavesdropping governments; and other parties who can monitor users' content from the point where the content leaves users' computers to within the data centers of these information accumulators. To achieve this goal, our framework proactively uses the principles of suppression of sensitive data and disinformation. Moreover, we use social-bots in a novel way for enhanced privacy and provide users' with plausible deniability for their photos, audio, and video content uploaded online.

Today's major concern is not only maximizing the information rate through linear network coding scheme which is intelligent combination of information symbols at sending nodes but also secured transmission of information. Though cryptographic measure of security (computational security) gives secure transmission of information, it results system complexity and consequent reduction in efficiency of the communication system. This problem leads to alternative way of optimally secure and maximized information transmission. The alternative solution is secure network coding which is information theoretic approach. Depending up on applications, different security measures are needed during the transmission of information over wiretapped network with potential attack by the adversaries. In this research work, mathematical model for different security constraints with upper and lower boundaries were studied depending up on the randomness added to the source message and hence the security constraints on linear network code for randomized source messages depends both on randomness added and number of random source symbols. If the source generates large number random symbols, lesser number of random keys can give higher security to the information but information theoretic security bounds remain same. Hence maximizing randomness to the source is equivalent to adding security level.