Abstracto

Investigations on Evolution of Strategies to Preserve Privacy of Moving Data Objects

P.Andrew, J.Anish Kumar, R.Santhya, Prof.S.Balamurugan, S.Charanyaa

This paper reviews methods to protect moving data objects for the past 30 years. Data Disclosure Preventing Techniques such as disclosure limiting and ad-hoc approval publishing data are depicted. Privacy Homomorphism And Encryption Methods such as Data Protection Directive, Commercial Masking facility algorithm, Data Encryption Algorithm and post randomization method are also discussed in detail. The Knowledge Discovery Data Mining Techniques to Preserve Privacy such as k-anonymity, Advanced Traveler Information Systems (ATIS) and Geographical Information System (GIS) are elaborately studied . Partition-And-Group Framework for Clustering Trajectories TRACLUS algorithm, secure verification proof gathering protocol (SLVPGP) and a large-scale quantitative analysis of Brightkite, a commercial location-based social network (LSN) are also elaborately studied. Decentralization Methods to Preserve Privacy Dummy Node and Cloaking Region Security Methods and Location Based Services for Securing Moving Data Objects are portrayed.