Association rule hiding in risk management for retail supply chain collaboration
Association rule hiding is an efficient solution that helps enterprises avoid the risk caused by sensitive knowledge leakage when sharing data in their collaborations. This study examines how data sharing has the potential to create risk for enterprises in retail supply chain collaboration and proposes a new algorithm to remove sensitive knowledge from the released database based on the intersection lattice of frequent itemsets. The proposed algorithm specifies the victim item such that the modification of this item causes the least impact on frequent itemsets and the non-sensitive association rule. In the experiment described in this paper, this algorithm is used in risk avoidance for a retailer sharing data in retail supply chain collaboration. The results indicate that our approach is applicable in a real context and outperforms previous mechanisms. (C) 2013 Elsevier B.V. All rights reserved.
association rule hiding risk management retail supply chain collaboration data sharing association rule mining