Research On Privacy-preserving Technologies In Distributed Environmen And Their Applications

Recently, as the growing security and privacy concerns, the technologies for privacy-preserving have developed prosperously. The technologies first mask the private data for privacy-preserving purpose, then, the masked data can be used to attend cooperative computation to obatin beneficial results. Generally speaking, the technologies for privacy-preserving can be classified into randomization and secure multiparty computation (SMC for short). Usually, randomization is more efficient but it cannot receive precise results. SMC requires more cost of communication and computation. Nevertheless, SMC always returns the precise values. Besides, SMC is stronger in security than randomization. Consequently, the research priorities in privacy-preserving area are to balance the security and efficiency and achieve secure and practical solutions. This dissertation will combine randomization with SMC to design novel privacy-preserving schemes. Furthermore, this dissertation proposes several secure schemes for the privacy-preserving problems in the area of distributed OLAP and text information hiding detecting etc. Additionally, effective and efficient security mechanisms are put forward to resist potential collusion attack.All in all, this dissertation studies the technologies for privacy-preserving from three levels:general theory and models, basic protocols and methods, of application protocol analysis and design. The main contributions and innovations in this paper are as follows.(1) Three novel different approaches to Privacy-preserving Add to Multiply Protocol (PPAtMP for short) are proposed, then it is confirmed that PPAtMP and scalar product protocol are equivalent to each other and one of them can be achieved via the other with the same communication and computation complexity. Then, this dissertation proposes secure two-party mean protocol, secure shared x\nx protocol and secure shared generic polynomial protocol based on scalar product protocol and PPAtMP.(2) A novel security model is defined to measure privacy-preserving protocol’s capability of resisting potential collusion. Then, this dissertation precisely analyzes several previous secure sum protocols’capability of resisting collusion and presents a novel adaptive collusion-resisting secure sum protocol. Theoretical analysis and experimental results confirm that the new scheme is efficient and has strong capability of resisting potential collusion. Besides, the new protocol’s capability of resisting collusion is adjustable according to different security needs. Additionally, this dissertation puts forward an efficient collusion-resisting privacy-preserving data aggregation protocol in wireless sensor network.(3) Referring to the people’s trust relationship model of Sociology and considering the dynamic, continuity and uncertainty of trust under the network environment, an adynamic trust evaluation model under distributed computing environment is presented, based on the Dempster-Shafer Theory and Shapley entropy. In the novel trust evaluation model, Shapley entropy evaluates the quantity of information of each node’s direct trust function, and then the direct trust is revised in consideration of both each node’s reliability and its quantity of information. Simulation experiments confirm that the new scheme can well adapt the dynamic behaviors of network nodes.(4) This dissertation also proposes novel privacy-preserving text information hiding detecting algorithm and privacy-preserving OLAP model based on SMC. The former enable text information hiding detecting algorithm to be securely deployed in a remote unconversant client. The secure scheme based on the latter model can achieve accurate results to OLAP aggregate queries.