Privacy preserving over data mining in distributed networks is still an important research issue in the field of Knowledge and data engineering or community based clustering approaches, privacy is an important factor while datasets or data integrates from different data holders or players for mining. Secure mining of data is required in open network. In this paper we are proposing an efficient ...

Ling Guo. Randomization Based Privacy Preserving Categorical Data Analysis. Under the direction of Dr. Xintao Wu The success of data mining relies on the availability of high quality data. To ensure quality data mining, effective information sharing between organizations becomes a vital requirement in today’s society. Since data mining often involves sensitive information of individuals, the pu...

In view of the issue of internal data in the construction of recommendation system may be leaked by external person. A privacy-preserving recommendation system based on MASK is designed to address it. The system consists of two parts: privacy-preserving subsystem and recommendation subsystem. First, disrupt original data to form new privacy-preserving data according to a certain probability. Se...

Privacy preserving mining of distributed data has numerous applications. Each application poses different constraints: What is meant by privacy, what are the desired results, how is the data distributed, what are the constraints on collaboration and cooperative computing, etc. We suggest that the solution to this is a toolkit of components that can be combined for specific privacy-preserving da...

The motivation of Privacy Preserving Data Mining (PPDM) is to obtain valid data mining results without access to the original sensitive information. The different privacy preserving technique on Perturbation based PPDM approach introduces random perturbation to individual values to preserve privacy before data are published. This proposed work is based on perturbation based privacy preserving d...

Protection of privacy from unauthorized access is one of the primary concerns in data use, from national security to business transactions. It brings out a new branch of data mining, known as Privacy Preserving Data Mining (PPDM). Privacy-Preserving is a major concern in the application of data mining techniques to datasets containing personal, sensitive, or confidential information. Data disto...

Title of Dissertation: Privacy Preserving Distributed Data Mining based on Multi-objective Optimization and Algorithmic Game Theory Kamalika Das, Doctor of Philosophy, 2009 Thesis directed by: Dr. Hillol Kargupta Professor Department of Computer Science and Electrical Engineering Use of technology for data collection and analysis has seen an unprecedented growth in the last couple of decades. I...

Title of Dissertation: Multiplicative Data Perturbation for Privacy Preserving Data Mining Kun Liu, Doctor of Philosophy, 2007 Dissertation directed by: Dr. Hillol Kargupta Associate Professor Department of Computer Science and Electrical Engineering Recent interest in the collection and monitoring of data using data mining technology for the purpose of security and business-related application...

Abstract— The increasing facility to track and collect large amounts of data with the use of this has led to an interest in the development of data mining algorithms which preserve user privacy. With the growth of data analysis and processing technique, the privacy disclosure problem about individual or company is inevitably exposed when releasing or sharing data to mine useful decision informa...