Privacy Preserving Updates to Personalized Anonymity Based Anonymous and Confidential Database

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Security
Format: PDF
Privacy of individual's information in datasets is main concern in the present technological phase. Thus it is becoming an increasingly important issue in many data mining applications in various fields like medical research, hospital records maintenance, intelligence agencies etc. Many previous papers have focused on generalization and suppression based anonymity which provides same amount of privacy preservation to all individuals. The paper focuses on devising private update techniques to database systems that supports notions of anonymity different than k-anonymity.
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