In this study, a new model is provided for customized privacy in privacy preserving data mining in which the data owners define different levels for privacy for different features. Additionally, in order to improve perturbation methods, a method combined of singular value decomposition (SVD) and feature selection methods is defined so as to benefit from the advantages of both domains. Also, to ...

This paper mainly deals with the issue of privacy preserving in data mining while collaborating n number of parties and trying to maintain confidentiality of all data providers details while collaborating their database. Here two type of attacks are addressed “insider attack” and “outsider attack”. In insider attack, the data providers use their own records and try to retrieve other data provid...

Data mining can be performed with four different directions Association, Clustering, Classification and the Bayesian formula. In the recent years, many privacy preserving techniques are developed. These techniques are used to provide the privacy to the data. Here privacy related various information is gathered with their brief introduction. Here mainly focus is on the classification decision tr...

Privacy is one of the most important properties of an information system must satisfy. In which systems the need to share information among different, not trusted entities, the protection of sensible information has a relevant role. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when data mining techniques are used in a malicious wa...

Huge volume of detailed personal data is regularly collected and sharing of these data is proved to be beneficial for data mining application. Such data include shopping habits, criminal records, medical history, credit records etc .On one hand such data is an important asset to business organization and governments for decision making by analyzing it. On the other hand privacy regulations and ...

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information used to feedback, increase revenue, cuts costs, or all. A number of freeware and shareware data mining software resources are available for analyzing data. Data Mining allows users or organizations to analyze the extracted data from many different dimensions or angles, systematica...

Privacy is defined as the freedom from unauthorized intrusion. The availability of personal information through online databases such as government records, medical records, and voters’ lists poses a threat to personal privacy. Intelligent search engines and data mining techniques further exacerbate the problem of privacy by simplifying access and retrieval of personal records. Data Obfuscation...

Privacy of information and security issues now-a-days has become the requisite because of big data. A novel framework for extracting and deriving information when the data is distributed amongst the multiple parties is presented by Privacy Preserving Data Mining (PPDM). The concern of PPDM system is to protect the disclosure of information and its misuse. Major issue with PPDM that exists is to...

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...