| Title | A Swarm-based Data Sanitization Algorithm in Privacy-Preserving Data Mining |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Wu, Jimmy Ming-Tai, Chun-Wei Lin, Jerry, Djenouri, Youcef, Fournier-Viger, Philippe, Zhang, Yuyu |
| Conference Name | 2019 IEEE Congress on Evolutionary Computation (CEC) |
| Keywords | artificial cost, Clustering algorithms, clustering methods, compositionality, data mining, data privacy, data protection, Data Sanitization, genetic algorithms, hiding failure, hierarchical clustering method, hierarchical clustering methods, Human Behavior, Itemsets, missing cost, multiobjective, multiobjective PSO, Optimization, Pareto solutions, particle swarm optimisation, pattern clustering, PPDM, privacy, privacy-preserving data mining, PSO, pubcrawl, resilience, swarm-based data sanitization algorithm |
| Abstract | In recent decades, data protection (PPDM), which not only hides information, but also provides information that is useful to make decisions, has become a critical concern. We present a sanitization algorithm with the consideration of four side effects based on multi-objective PSO and hierarchical clustering methods to find optimized solutions for PPDM. Experiments showed that compared to existing approaches, the designed sanitization algorithm based on the hierarchical clustering method achieves satisfactory performance in terms of hiding failure, missing cost, and artificial cost. |
| DOI | 10.1109/CEC.2019.8790271 |
| Citation Key | wu_swarm-based_2019 |
A Swarm-based Data Sanitization Algorithm in Privacy-Preserving Data Mining