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Online Social Network (OSN) data holders like Facebook, Twitter, Linked-In release their data to third parties such as researchers, data mining practitioners etc. Third parties mine the released data and help data holders gain deeper insights about the network. Releasing the social network graph in its actual form results in loss of privacy. As a result OSN users could end up losing trust that they...
In our prior work, we identified rules for use in recommendation algorithms on Online Social Network (OSN) in order to increase the relevance of content suggested to a user. The resulting recommendation algorithms filter out and prioritize event types for OSN users (such as photo posts by friends, status posts, shared content, etc.), and are thereby intended to reduce information overload. This paper...
In this paper, we tackle the problem of graph generalization in the context of privacy-preserving social network mining. By grouping together nodes that are not only similar but that also belong to the same k-shells, we better preserve the community structure of the graph, its utility in case of clustering-related applications, while still achieving some privacy level through the concept of graph...
Location privacy is an important issue in location-based services. A large number of location cloaking algorithms have been proposed for protecting location privacy of users. However, these algorithms cannot be used in vehicular networks due to constrained vehicular mobility. In this paper, we propose a new method named Protecting Location Privacy with Clustering Anonymization (PLPCA) for location-based...
Rapid development of web 2.0 and social networks brings convenience for users' information sharing. The thriving of information sharing inevitably leaves users' private information vulnerable to leakage. Weighted social networks can provide more personal information than unweighted social networks, such as those weight based information. Weight based information (weight distribution, shortest paths...
The development of several popular social networks in recent days and publication of social network data has led to the danger of disclosure of sensitive information of individuals. This necessitated the preservation of privacy before the publication of such data. There are several algorithms developed to preserve privacy in micro data. But these algorithms cannot be applied directly as in social...
Although a lot of literatures have been proposed on the issue of privacy preserve with relational data, social networks bring new challenges of resisting re-identify attacks. Based on message passing, an approach of privacy preserve in social networks is proposed in this paper. Individuals are assigned to different clusters according to their quasi-identifies and structural similarity measured by...
The(P, α, K) anonymity model for privacy protection of personal information in the social networks is proposed in this paper. The hidden fields P and the hidden levels a are set according to theindividual privacy needs of the users. Then make the released data to meet the privacy protection requirements through the Datafly algorithm and the clustering algorithm. The experimental data shows that the...
Social networks applications have become popular for sharing information. Social networks data usually contain users'private information. So privacy preservation technologies should be exercised to protect social networks against various privacy leakages and attacks. In this paper, we give an approach for anonymizing social networks which can be represented as bipartite graphs. We propose automorphism...
Online Social Networks (OSNs) are becoming more important in the web 2.0 paradigm. Although most implementations of OSN are not distributed applications, users conforming an OSN work autonomously posting their information in the OSN and interacting among them. Users are responsible of the information they post in their profile and, in the vast majority of social networks, they can limit the disclosure...
The flow of information in the network currently existing attacks and malicious damage, a privacy protection algorithm based on the maximum greedy is proposed, the data privacy acts as weights between nodes in network diagram , change these weights to achieve the protection of important data, by obtaining the shortest path way to ensure that efficiency is not influenced ,the experimental results show...
Sharing personal information and documents is pervasive in Web 2.0 environments, which creates the need for properly controlling shared data. Most existing authorization and policy management systems are for organizational use by IT professionals. Average Web users, however, do not have the sophistication to specify and maintain privacy policies for their shared content. In this paper, we aim to utilize...
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