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Amelioration of Anonymity Modus Operandi for Privacy Preserving Data Publishing
Abstract
The scientific tumultuous intonation has swept our feet's, of its balance and at the same time wheedled us to reach the take-off arena from where we can march equipped and outfitted into the subsequent century with confidence & self-assurance; by unearthing solutions for all information security related issues (with special emphasis on privacy issues). Examining various outstanding research problems that encompass to be embarked upon for effectively managing and controlling the balance between privacy and utility, the research community is pressurized to propose suitable elucidations. The solution is to engender several Privacy-Preserving Data Publishing (PPDP) techniques like Perturbation, swapping, randomization, cryptographic techniques etc., Amongst the various available techniques k-anonymity is unique in facet of its association with protection techniques that preserve the truthfulness of the data. The principal chip in of this sketch out comprises: 1) Motivation for this exploration for Amelioration Of Anonymity Modus Operandi For Privacy Preserving Data Mining; 2) investigation of well-known research approaches to PPDM; 3) argue solutions to tackle the problems of security threats and attacks in the PPDM in systems; 4) related survey of the various anonymity techniques; 5) exploration of metrics for the diverse anonymity techniques; 6) performance measures for the various anonymity techniques; and 7) contradistinguish the diverse anonymity techniques and algorithms.
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