An integrated method for hiding sensitive association rules of the supply chains
Hui Chao Cheng, Wenjie Zhang, Zhaoyang Wang, Fengjuan Zuo, Zaifang Zhang · IET Collaborative Intelligent Manufacturing · 2021
Abstract Sensitive association rule hiding is an important issue of data sharing for supply chains, which can ensure mutual benefits and avoid information leakages among different enterprises. An integrated method is proposed by using Apriori and the discrete binary particle swarm optimization (BPSO) algorithm, aiming to improve the rule hiding efficiency and effectiveness. The Apriori algorithm is used to extract the association rules from sharing data. The selected sensitive association rules can be hidden using BPSO based on constructing discrete binary space and multi‐objective fitness functions. The proposed method is verified through a case study. The results show that the proposed method can effectively hide sensitive information and protect enterprises' business benefits.