期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：10
出版社：S.S. Mishra
摘要：Every Organization sends the data to researchers for the mining purpose. This may affect the privacy of an individual. There are different privacy measures to protect the individual's data. One of the privacy measures is k-anonymity. The k-anonymity property does not protect the data against attribute disclosure. The p-sensitive k-anonymity property overcomes this problem. But it is insufficient to prevent Similarity Attack.The(p, ∝)-sensitive k-anonymity and (p+, ∝)-sensitive k-anonymity overcomes this problem but there is heavy information loss. In the present work Probabilistic Anonymization is introduced to reduce the information loss because it reveals the information about the non secret category which is not much sensitive
