Privacy Preserving in Data Mining using FP Growth Algorithm on Hybrid Partitioned Dataset
نویسندگان
چکیده
منابع مشابه
Approximate Privacy-Preserving Data Mining on Vertically Partitioned Data
In today’s ever-increasingly digital world, the concept of data privacy has become more and more important. Researchers have developed many privacy-preserving technologies, particularly in the area of data mining and data sharing. These technologies can compute exact data mining models from private data without revealing private data, but are generally slow. We therefore present a framework for...
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With the proliferation of information available in the internet and databases, the privacypreserving data mining is extensively used to maintain the privacy of the underlying data. Various methods of the state art are available in the literature for privacypreserving. Evolutionary Algorithms (EAs) provide effective solutions for various real-world optimization problems. Evolutionary Algorithms ...
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Micro data is a valuable source of information for research. However, publishing data about individuals for research purposes, without revealing sensitive information, is an important problem. The main objective of privacy preserving data mining algorithms is to obtain accurate results/rules by analyzing the maximum possible amount of data without unintended information disclosure. Data sets fo...
متن کاملPrivacy Preserving Data Mining over Vertically Partitioned Data
Vaidya, Jaideep Shrikant. Ph.D., Purdue University, August, 2004. Privacy Preserving Data Mining over Vertically Partitioned Data. Major Professor: Chris Clifton. The goal of data mining is to extract or “mine” knowledge from large amounts of data. However, data is often collected by several different sites. Privacy, legal and commercial concerns restrict centralized access to this data. Theore...
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Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. This paper presents privacy preserving association rule mining across vertically partitioned data. We present an efficient algorithm to discover association rules with minimum levels of support and confidence, from heterogeneous data distributed across 2 parties, while preventing eit...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2016
ISSN: 0975-8887
DOI: 10.5120/ijca2016911021