Secure Collaborative Data Publishing by Using Computation Trusted Third-Party Protocols

In this paper the collaborative data publishing issue for horizontally Partitioned data at different data providers was discussed. The attackers by colluding data from multiple providers, who use their own data to publish, were considered by implementing the two methods to improve the privacy constraints and secure in data publish. Initially, the Hidden Markov Models (HMM) is used to analysis the non-authenticated user who are trying to access the data is implemented to overcome the m-privacy notations which doesn’t satisfies the privacy constraints against the group of colluding the different data providers in existing design, Second the Attribute based anonymity for preserving privacy is used for checking strategies and adaptive privacy of individuals in organisation’s publishing of data was implemented