Identity Based Private Matching
Zhongsheng Wu, Zhide Chen, Fuchun Guo, Li Xu · 2007
There is an increasing need for privately matching data across autonomous entities. Practical private matching applications often require respecting privacy limits and enforcing correctness simultaneously. However, existing schemes have substantial weakness and do not meet the requirement. In this paper, we propose a new private matching scheme based on bilinear paring in a public key system: Identity Based Private Matching (IBPM). Our scheme guarantees the privacy of users. We also address the spoofing problem by the use of Data Ownership Parameters (DOP) that can attest to the ownership of data in a database.