Ethical and social issues in the information age
Ethical and social issues in the information age
Computer and Information Ethics
Computer and Information Ethics
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Disclosure Limitation of Sensitive Rules
KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
IEEE Transactions on Knowledge and Data Engineering
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy Preserving Clustering on Horizontally Partitioned Data
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
A pioneering cryptic random projection based approach for privacy preserving data mining
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Low Dimensional Data Privacy Preservation Using Multi Layer Artificial Neural Network
International Journal of Intelligent Information Technologies
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Computing is an ogle spectator witnessing afloat similar to a tornado. The chic data analysis and mining techniques compromise privacy and their exploitation have reached the pinnacle, demanding our attention. Amongst the available diverse techniques available for privacy preservation, the existing techniques involve only individual preservations. This work proposes novel three-tier architecture. The subsequent coalescing of three best secure techniques endows us with a three-fold privacy preservation, namely access control limitation technique, randomisation and Privacy Preserving Clustering (PPC). Thus, our framework gives an efficient control system comprising authentication, authorisation and access for each database application; efficiency and economical benefits of randomisation and advantages of PPC. We have further proposed a method for computing the object-based dissimilarity for secure computation for all different attribute types. PPC uses a combination of CLARANS with Simulating Annealing in order to achieve increased privacy, efficient scaling and improvised performance.