Beyond the ongoing privacy preserving social network studies which mainly focus on node de-identification and link protection, this paper is written with the intention of preserving the privacy of link's affinities, or weights, in a finite and directed social network. To protect the weight privacy of edges, we define a privacy measurement, k-anonymity, over individual weighted edges. It is cons...

Online social networks and publication of social network data has led to the risk of leakage of confidential information of individuals. This requires the preservation of privacy before such network data is published by service providers. Privacy in online social networks data has been of utmost concern in recent years. Hence, the research in this field is still in its early years. Several publ...

Access control mechanisms protect sensitive information from unauthorized users. However, when sensitive information is shared and a Privacy Protection Mechanism (PPM) is not in place, an authorized user can still compromise the privacy of a person leading to identity disclosure. A PPM can use suppression and generalization of relational data to anonymize and satisfy privacy requirements, e.g.,...

In 2009, a non-iterative privacy preservation for online lotteries is proposed in IET Information Security by J.S lee, C.S Chan and C.C Chang [1], who claim their scheme achieve the following properties:  Privacy. No one can learn the choices made by lottery players except the players themselves.  Security. No one can counterfeit a winner or forge a winning lottery ticket to claim the prize. ...

In this paper, we propose new ideas to protect user privacy while allowing the use of a user history graph. We define new privacy notions for user history graphs and consider algorithms to generate a privacy-preserving digraph from the original graph.

w w w . i j c s t . c o m InternatIonal Journal of Computer SCIenCe and teChnology 485 Abstract Applications in commercial domains possess large datasets on individuals. This data includes private and sensitive information e.g. patient diseases, bank account details, organization structural details etc. When data mining techniques are applied on these applications the private and sensitive info...

We are experiencing the expanding use of location-based services such as AT&T TeleNav GPS Navigator and Intel’s Thing Finder. Existing location-based services have collected a large amount of location data, which have great potential for statistical usage in applications like traffic flow analysis, infrastructure planning and advertisement dissemination. The key challenge is how to wisely use t...

Privacy is an important issue when one wants to make use of data that involves individuals’ sensitive information. Research on protecting the privacy of individuals and the confidentiality of data has received contributions from many fields, including computer science, statistics, economics, and social science. In this paper, we survey research work in privacy-preserving Data Publishing and Ass...

Privacy perservation, in terms of sensitive data access and management, is an important feature of decentralized calendar systems. Indeed, when users delegate their sensitive data such as timetables to an autonomous agent, this one executes many automatic data processing without their intervention: users lost a part of their data control. To tackle this problem, we propose in this article to ex...

The development in data mining technology brings serious threat to the individualinformation. The objective of privacy preserving data mining (PPDM) is to safeguard the sensitive information contained in the data. The unwanted disclosure of the sensitive information may happen during the process of data mining results. In this paper we identify four different types of users involved in mining a...