IMPROVEMENT OF CUCKOO ALGORITHM FOR ASSOCIATION RULE HIDING PROBLEM

Abstract

Nowadays, the problem of data security in the process of data mining receives more attention. The question is how to balance between exploiting legal data and avoiding revealing sensitive information. There have been many approaches, and one remarkable approach is privacy preservation in association rule mining to hide sensitive rules. Recently, a meta-heuristic algorithm is relatively effective for this purpose, which is cuckoo optimization algorithm (COA4ARH). In this paper, an improved version of COA4ARH is presented for calculating the minimum number of sensitive items which should be removed to hide sensitive rules, as well as limit the loss of non-sensitive rules. The experimental results gained from three real datasets showed that the proposed method has better results compared to the original algorithm in several cases.

Keywords

• ẩn luật nhạy cảm
• khai thác dữ liệu đảm bảo sự riêng tư
• tác dụng phụ
• thuật toán tối ưu hóa cuckoo.