Volume 4, Issue 6

Degree Smoothing On Social Networks against Frequent Shared Patterns.


K. Anusha* and K. Venkata Ramana


Advances in technology has made it possible to collect data about individuals and connections between them, such as Email correspondence and friendship. Researchers that have collected such social network data often have a compelling interest in allowing others to analyze the data. However sharing such kind of private information to the public will result in unacceptable disclosure. In this paper we present a framework of, how to provide privacy to individuals in a social network against the adversary from frequent shared patterns. We propose Degree Smoothing method by applying Anonymization and Isomorphism techniques. By taking real world examples we prove that, we can reduce the threat of frequent shared patterns in a social network.



PAGES : 435-439 | 38 VIEWS | 79 DOWNLOADS

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K. Anusha* and K. Venkata Ramana | Degree Smoothing On Social Networks against Frequent Shared Patterns. | DOI : https://doi.org/10.62226/ijarst20150642

Journal Frequency: ISSN 2320-1126, Monthly
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Acceptance Notification: Within 6 days
Subject Areas: Engineering, Science & Technology
Publishing Model: Open Access
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