An Efficient Algorithm for Sequential Pattern Mining with Privacy Preservation.

This paper presents an index-based algorithm named SSAPP for exploring frequent sequential patterns in a distributed environment with privacy preservation. The SSAPP algorithm uses an equivalent form of a sequential pattern to reduce the number of cryptographic operations, such as decryption and encryption. In order to improve the efficiency of sequential pattern mining, the SSAPP algorithm keeps track of patterns in a tree data structure called SS-Tree. This tree is used to compress and represent sequences from a sequence database. Moreover, a SS-Tree allows one to obtain frequent sequential patterns without generation of candidate sequences. The conducted experiments show the effectiveness of the proposed approach. The SSAPP algorithm greatly reduces the number of cryptographic operations and it has good scalability.