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...Show MoreMetadata
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.
Published in: 2019 IEEE Congress on Evolutionary Computation (CEC)
Date of Conference: 10-13 June 2019
Date Added to IEEE Xplore: 08 August 2019
ISBN Information: