文章基本信息

标题：A Hybrid Approach to Preserving Privacy in Data Mining using L-K-C and personalized Privacy
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作者：Rahul Pandey ; Shilpa Jain
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：2
页码：1191
DOI：10.15680/IJIRCCE.2018.0602098
出版社：S&S Publications
摘要：Owing to the massive amounts of data being collected in every fraction of second, there lie threats to theconfidentiality, privacy and authenticity of the information being transmitted. Due to ease of access to the data byanyone, a serious concern for privacy has arisen. Thus, in order to safeguard the information leakage to hackers, thereare several techniques being practiced. The central issue with these techniques is that while maintaining the privacy,they tend to also increase the information loss.In this paper we present a new and hybrid approach to preserve privacyin data mining. Our model discusses about different privacy models and make a hybrid version out of it. The evaluationof the model’s results show that we have obtained a significant decrease in information loss that occurs due to privacycompared to many other existing models. Thus, we propose a methodology to preserve data, without any hindrance inprivacy, and at the same time maintaining the information and the utility balance.We will take data from hospital’sdatabase which will contain the data of the patients who got their treatment there. We assume that the intruder is havingaccess to AADHAR list. As we will show in this paper it is not very difficult to link Aadhar list with patient’s data andget access to sensitive information of the patient.
关键词：Preserving Privacy; Data Mining; Quasi Identifier; Personalized privacy; Sensitive information;Aadhar; Hybrid; Utility