Privacy Preserving Data Mining: Techniques, Classification and Implications - A Survey
نویسندگان
چکیده
منابع مشابه
the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance
با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...
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Privacy preserving becomes an important issue in the development of various data mining techni'ques. In this paper, we have discussed various techniques to preserve privacy while mining data. In the absence of uniform framework across all data mining techniques, researchers have focused on data technique specific privacy preserving issue. Available framework and algorithms provide further insig...
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Data mining is the process of extraction of data from large database. One of the most important topics in research community is Privacy preserving data mining (PPDM). Privacy preserving data mining has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes. It is essential to maintain a ratio between privacy protection and knowledge discovery. To s...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2016
ISSN: 0975-8887
DOI: 10.5120/ijca2016909006