Comparative Study on Perturbation Techniques in Privacy Preserving Data Mining on Two Numeric Datasets
نویسندگان
چکیده
منابع مشابه
A Study on Data Perturbation Techniques in Privacy Preserving Data Mining
Student, Dept. Of Computer Engineering, Grow More Faculty of Engineering Himatnagar, Gujarat, India Asst. Professor, Dept. of Computer Engineering, Grow More Faculty of Engineering Himatnagar, Gujarat, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract-In recent years, the data mining techniq...
متن کاملA Study on Normalization Techniques for Privacy Preserving Data Mining
Abstract Data mining is a prevailing technique which extracts the unfamiliar appealing patterns from large data sets. The extracted facts are utilized in various domains like marketing, weather forecasting, and medical diagnosis. It is very vital that the data gets exposed when the organizations start sharing the data for the mining process and privacy may be breached. Privacy is becoming a mor...
متن کاملGeometric Data Perturbation Techniques in Privacy Preserving On Data Stream Mining
Data mining is the information technology that extracts valuable knowledge from large amounts of data. Due to the emergence of data streams as a new type of data, data stream mining has recently become a very important and popular research issue. Privacy preservation issue of data streams mining is very important issue, in this dissertation work, an approach based on Geometric data perturbation...
متن کاملOn Random Additive Perturbation for Privacy Preserving Data Mining
Title of Thesis: On Random Additive Perturbation for Privacy Preserving Data Mining Author: Souptik Datta, Master of Science, 2004 Thesis directed by: Dr. Hillol Kargupta, Associate Professor Department of Computer Science and Electrical Engineering Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving...
متن کاملOn the Privacy Preserving Properties of Random Data Perturbation Techniques
Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving data mining techniques. A large fraction of them use randomized data distortion techniques to mask the data for preserving the privacy of sensitive data. This methodology attempts to hide the sensitive data by randomly modifying the data values ofte...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Innovative Computing
سال: 2018
ISSN: 2180-4370
DOI: 10.11113/ijic.v8n1.161