Privacy is main concern in the present technological phase in the world. Information security has become a dangerous issue since the information sharing has a common need. Thus privacy is becoming an increasingly important issue in many data mining applications in numerous fields like medical research, intelligence agencies, hospital records maintenance etc. The paper focuses on survey on privacy preserving on anonymous database and on devising private update techniques to database systems that supports notions of anonymity diverse than k-anonymity. The existing methods delivers the same amount of privacy for all persons, and may be offering insufficient protection to a subset of people, while applying excessive privacy control to another subset. Motivated by these the concept of personalized anonymity is used which performs the least generalization for satisfying everybody's requirements, and thus, retains the largest amount of information from the microdata. To preserve privacy and confidentiality with minimum loss of information an approach on generalization based on personalized anonymity method to protect privacy of individual is proposed.
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