Abstract:

A privacy-preserving set intersection cardinality computation protocol based on semi-trusted third party and commutative encryption is developed, which can be used to slove the privacy-preserving computational problems, such as information entropy computation and conditional information entropy computation. A privacy-preserving attribute reduction algorithm based on conditional information entropy for the vertically partitioned multi-decision tables is proposed.The algorithm can compute globally valid attribute reduction using the attribute reduction idea based on information viewpoint of Rough set theory, which can get accurate attribute reduction effect in the premise of no sharing of private information among participators. Analysis results show the proposed algorithm is efficient.

Key words: attribute reduction; privacy preserving; secure multi-party computation; Rough set; conditional information entropy