A Hybrid Algorithm for Privacy Preserving in Data Mining

Sridhar Mandapati, Raveendra Babu Bhogapathi, Ratna Babu Chekka
2013 International Journal of Intelligent Systems and Applications  
With the proliferat ion of information available in the internet and databases, the privacypreserving data min ing is extensively used to maintain the privacy of the underlying data. Various methods of the state art are available in the literature for privacypreserving. Evo lutionary Algorith ms (EAs) provide effective solutions for various real-world optimization problems. Evolutionary Algorith ms are efficiently emp loyed in business practice. In privacy-preserving domain, the e xisting EA
more » ... utions are restricted to specific problems such as cost function evaluation. In this work, it is proposed to implement a Hybrid Evolutionary Algorith m using Genetic A lgorith m (GA) and Particle Swarm Optimizat ion (PSO). Both GA and PSO in the proposed system work with the same population. In the proposed framework, k-anonymity is accomplished by generalization of the original dataset. The hybrid optimizat ion is used to search for optimal generalized feature set. Anonymity transforms data to equivalence classes and each class has a set of K-records indistinguishable fro m each other [7] [8] [9] . Problems with this approach were remedied using techniques like l-d iversity and tcloseness [10, 11] .
doi:10.5815/ijisa.2013.08.06 fatcat:wygohca2mzes7bhngsfmzpgjlm