2019
DOI: 10.35940/ijitee.j8792.0881019
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K-Anonymity Enhancement for Privacy Preservation with Hybridization of Cuckoo Search and Neural Network using Clustering

Abstract: Expansion of social network and the publication of its data have directed the risk of disclosure of individuals’ confidential information. Privacy preservation is a must thing before service providers publish the network data. In recent years, privacy in social network data has become the most concerned issue as it has gripped our lives in a dramatic manner. Numerous anonymization methods are there that assists in privacy preservation of social networking and among all, kanonymity is the utmost one that helps … Show more

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Cited by 1 publication
(1 citation statement)
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References 19 publications
(36 reference statements)
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“…In this strategy, approximately 2.4% area deviation is observed on average among the layers. Kaur et al [15] propose Cuckoo search based meta-heuristic approach for achieving efficient net list partitioning in 3D IC. Experimental results show that this cuckoo search based approach achieves considerable reduction in the number of interconnection and computational time.…”
Section: Past Workmentioning
confidence: 99%
“…In this strategy, approximately 2.4% area deviation is observed on average among the layers. Kaur et al [15] propose Cuckoo search based meta-heuristic approach for achieving efficient net list partitioning in 3D IC. Experimental results show that this cuckoo search based approach achieves considerable reduction in the number of interconnection and computational time.…”
Section: Past Workmentioning
confidence: 99%