COMATS: a cuckoo-mimicking data anonymization scheme for preserving sensitive preferences in transaction data

Abstract

Sharing customer transaction data is becoming more perceived in e-commerce and retail industries. Even though the act derives benefits for companies, it may end up in certain privacy threats, such as sensitive personal preferences disclosure. Therefore, the data owner should take measures to minimize the threats. Data anonymization is one of the solutions that has been suggested to address the issue. However, there are still underlying problems, specifically in diminishing the amount of information loss and item loss, as well as maintaining data properties of the anonymized dataset. This paper proposes a unique data anonymization scheme called COMATS. It adopts the brood parasitism behavior of cuckoo birds in laying their eggs into host nests. The scheme incorporates item insertion technique and item suppression technique. The robustness of the proposed scheme lies in its strategy for selecting suppressed items and determining the inserted items. To ensure its efficacy, the proposed method is evaluated in several experiments. The experimental results suggest that the COMATS can guarantee privacy protection by reducing the probability of a successful attack. Additionally, it can also reduce the number of item losses and preserve better data utility in comparison to existing data anonymization schemes.