PTA: An Efficient System for Transaction Database Anonymization

• Main Authors: Jerry Chun-Wei Lin, Qiankun Liu, Philippe Fournier-Viger, Tzung-Pei Hong
• Format: Article
• Language: English
• Published: IEEE 2016-01-01
• Series: IEEE Access
• Subjects: Anonymity; TSP; divide-and-conquer; Gray sort; privacy preserving data mining
• Online Access: https://ieeexplore.ieee.org/document/7552454/

Several approaches have been proposed to anonymize relational databases using the criterion of k-anonymity, to avoid the disclosure of sensitive information by re-identification attacks. A relational database is said to meet the criterion of k-anonymity if each record is identical to at least (k - 1) other records in terms of quasi-identifier attribute values. To anonymize a transactional database and satisfy the constraint of k-anonymity, each item must successively be considered as a quasi-identifier attribute. But this process greatly increases dimensionality, and thus also the computational complexity of anonymization, and information loss. In this paper, a novel efficient anonymization system called PTA is proposed to not only anonymize transactional data with a small information loss but also to reduce the computational complexity of the anonymization process. The PTA system consists of three modules, which are the Pre-processing module, the TSP module, and the Anonymity model, to anonymize transactional data and guarantees that at least k-anonymity is achieved: a pre-processing module, a traveling salesman problem module, and an anonymization module. Extensive experiments have been carried to compare the efficiency of the designed approach with the state-of-the-art anonymization algorithms in terms of scalability, runtime, and information loss. Results indicate that the proposed PTA system outperforms the compared algorithms in all respects.