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A Novel Approach to Evade Attacks in Online Social Networks

Published: 26 November 2016 Publication History

Abstract

Anonymization of published social network data has become an important research topic nowadays. The major concern is to publish data of individuals in such a manner that the released table not only provides the essential information to be used by researchers but also prevents the disclosure of sensitive information. Various techniques like K-anonymity, L-diversity and T-closeness have been proposed to achieve anonymization of the data. K-anonymity suffers from various limitations such as it cannot prevent attribute disclosure and also results in homogeneity and background knowledge attacks. This paper mainly deals with handling these two attacks that break the privacy constraints of K-anonymity. The proposed technique has been evaluated using real-time database gathered from Twitter social network. Experimental results show that the proposed technique not only prevents identity and attribute disclosure but at the same time is capable of handling attacks on K-anonymity by resulting in minimum information loss to the original data.

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  1. A Novel Approach to Evade Attacks in Online Social Networks

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      cover image ACM Other conferences
      ICCNS '16: Proceedings of the 6th International Conference on Communication and Network Security
      November 2016
      133 pages
      ISBN:9781450347839
      DOI:10.1145/3017971
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      Publication History

      Published: 26 November 2016

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      Author Tags

      1. Anonymization
      2. Background knowledge attack
      3. Homogeneity attack
      4. K-anonymity
      5. Sensitive attributes
      6. Twitter

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