Review on privacy-preserving data comparison protocols in cloud computing

Data comparison is a crucial step in many operations, including data mining, data classification, image feature extraction, and image retrieval. With the existing data encryption technology, encrypted data computation and encrypted data comparison can be executed; however, there is no single data encryption method can meet the challenge of tackle the two tasks at the same time. Therefore, in many data operations, two major steps are involved: one is to encrypt the data with a computation supporting encryption method; one is to construct a comparison protocol to conduct privacy-preserving data comparison. While the first step has become a fast-developing and systematic research spot, research in the second step area remains scattered. In this chapter, we focus on the latter, by conducting an in-depth review of the development of the privacy-preserving data comparison. We introduce and analyze several most commonly used privacy-preserving data comparison protocols and their application scenarios; then we examine their functionality, security, computation complexity and communication overhead. By a systematic investigation of these protocols, we reveal and define the security challenge underneath each protocol. Our findings provide systematic and in-depth reference for improvement of the existing data comparison protocols in cloud environment.