The mashup of microdata sources to form a data hub must fulfill a set of privacy preservation anonymity requirements that hinder data analysts to figure out sensitive information of the source datasets. This is relevant in a number of fields that include smart cities, electronic healthcare records and others. Linked data publishing architectures are not designed to adapt well to the requirement...

Privacy preserving data publishing (PPDP) methods a new class of privacy preserving data mining (PPDM) technology, has been developed by the research community working on security and knowledge discovery. It is common to share data between two organizations in many application areas. When data are to be shared between parties, there could be some sensitive patterns which should not be disclosed...

In Vehicular Ad-hoc networks are networks of communication between vehicles and roadside units and inter vehicle units. It can be used to provide traffic management, route planning, and identifying roadside units using short-range wireless communication. This network has the potential to increase safety system and it can provide many services to drivers, but they also present risks to privacy a...

Privacy Preserving Data Mining is a method which ensures privacy of individual information during mining. Most important task involves retrieving information from multiple data bases which is distributed. The data once in the data warehouse can be used by mining algorithms to retrieve confidential information. The proposed framework has two major tasks, secure transmission and privacy of confid...

This position paper first summarizes work done by the first author on location privacy and differential privacy. These techniques will help to solve privacy problems in decentralized mobile social networks, which is the main theme of his PhD research. The paper then briefly reviews the state-of-the-art in privacy-preservation of social graphs and clarifies the lack of attention to graph sharing...

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...

Access Control Mechanisms (ACM) are used to ensure that only authorized information is available to users. However, sensitive information can still be misused by authorized users to compromise the privacy of consumers. The concept of privacy-preservation for sensitive data can require the enforcement of privacy policies or the protection against identity disclosure by satisfying some privacy re...

Recently big data has become a hot research topic. The rising amounts of big data also increase the chance of violate the privacy of individuals. Since big data need high computational power and large storage, distributed systems are used. As multiple parties are concerned in these systems, the risk of privacy violation is improved. There have been a number of privacy-preserving methods develop...

Cryptography is to become familiar with the requirement of large, complex, information rich data sets for it’s privacy preservation. The privacy preserving data mining has been generated; to go through the concept of privacy in data mining is hard. Several algorithms and approaches are being generated theoretically, but practically it is hard. Privacy in data mining can be achieved through seve...

In various distributed data mining settings, leakage of the real data is not adequate because of privacy issues. To overcome this problem, numerous privacy-preserving distributed data mining practices have been suggested such as protect privacy of their data by perturbing it with a randomization algorithm and using cryptographic techniques. In this paper, we review and provide extensive survey ...