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An Enhanced Design for Anonymization in Social Networks


  • Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham (University) Amrita Nagar P.O, Ettimadai, Coimbatore 641112, Tamil Nadu, India


Objectives: Our primary objective is to safeguard the privacy of the users by anonymizing the sensitive data shared by the users in Social networking sites. Methods/Statistical Analysis: The user's friends are grouped dynamically into various categories such as best friends, normal friends and casual friends based on their closeness with the user. The most private sensitive data is solely disclosed to best friends, while the sensitive data is anonymized using generalization and revealed to the normal friends. The last category of friends is exposed to only the least private information using another level of generalization. Findings: Currently, Social networking sites have become the rapid and preferred way of communicating with each other to share information. On one hand the options and benefits expand constantly, while on the other data privacy risks and sensitivity issues accumulate, eventually the privacy of the user is at grave, our work addresses this issue. The proposed design is resilient to Sybil attacks, where it restricts the revelation of the sensitive data of the user by anonymizing the shared data among various categories of friends. Application/Improvement: The performance of the system is enhanced by restricting the access to the sensitive data among various categories of friends based on their closeness degree.


Automated Grouping, Data Analysis, Generalization, Privacy Protection, Sensitive Sentiments, Social Networking Sites.

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  • Li Y. Survey on situation of Chinese college students choosing to use social networking. In: Computer Research and Development (ICCRD), 2011 3rd International Conference; 2011 Mar. p. 344-348.
  • LeBlanc D, Biddle R. Risk perception of internet-related activities. In: Privacy, Security and Trust (PST), 2012 Tenth Annual International Conference; 2012. p. 88-95.
  • Zamzami IF, Olowolayemo A, Bakare KK, Kind DA. Sensitivity to online privacy in social networking sites. In: Information and Communication Technology for the Muslim World (ICT4M), 2010 International Conference; 2010 Dec. p. B-21-26.
  • Nagle F, Singh L. Can friends be trusted? Exploring privacy in online social networks. In: Social Network Analysis and Mining, 2009. ASONAM’09. International Conference on Advances; 2009 Jul. p. 312-315.
  • Hoens TR, Blanton M, Chawla NV. A private and reliable recommendation system for social networks. In: Social Computing (SocialCom), 2010 IEEE Second International Conference, IEEE; 2010 Aug. p. 816-825.
  • Al Hasib A. Threats of online social networks. IJCSNS International Journal of Computer Science and Network Security. 2009 Nov; 9(11):1-6.
  • Fire M, Goldschmidt R, Elovici Y. Online social networks: threats and solutions. Communications Surveys and Tutorials, IEEE. 2014 Jan; 6(4):2019-2036.
  • Ur B, McGrath R. Grouping Friends for Access Control in Online Social Networks, p. 1-17.
  • Zhe Z, Li Z. A method of visualizing friend relations and recommending groups in online social network. In: Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference; 2012 May. p. 836-839.
  • Tanbeer SK, Jiang F, Leung CK, MacKinnon RK, Medina IJ. Finding groups of friends who are significant across multiple domains in social networks. In: Computational Aspects of Social Networks (CASoN), 2013 Fifth International Conference; 2013 Aug. p. 21-26.
  • Zhou L. Trust based recommendation system with social network analysis. In: 2009 International Conference on Information Engineering and Computer Science; 2009 Dec. p. 1 – 4.
  • Qian C, Xiao X, Chen S, Wang X. Grouping friends to improve privacy on Social Networking Sites. In: Conference Anthology; 2013 Jan. p. 1-6.
  • Can AB, Bhargava B. Sort: A self-organizing trust model for peer-to-peer systems. Dependable and Secure Computing, IEEE Transactions. 2013 Jan; 10(1): 14-27.
  • Samuel SJ, Dhivya B. An efficient technique to detect and prevent Sybil attacks in social network applications. In: Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference; 2015 Mar. p. 1-3.
  • Shishodia MS, Jain S, Tripathy BK. GASNA: greedy algorithm for social network anonymization. In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining; 2013 Aug. p. 1161-1166.
  • Wang Z, Liao J, Cao Q, Qi H, Wang Z. Friend book: a semantic-based friend recommendation system for social networks. Mobile Computing, IEEE Transactions. 2015 Mar; 14(3):538-551.
  • Machanavajjhala A, Kifer D, Gehrke J, Venkitasubramaniam M. l-diversity: Privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data (TKDD). 2007 Mar; 1(1) .
  • Li N, Li T, Venkata Subramanian S. t-closeness: Privacy beyond k-anonymity and l-diversity. In: Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference; 2007 Apr. p. 106-115.
  • Babour A, Khan JI. Tweet Sentiment Analytics with Context Sensitive Tone-Word Lexicon. In: Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), IEEE Computer Society; 2014 Aug. p. 392-399.
  • Akaichi J. Social Networks’ Facebook’ Statutes Updates Mining for Sentiment Classification. In: Social Computing (SocialCom), 2013 International Conference; 2013 Sep. p. 886-891.
  • Bahrainian SA, Liwicki M, Dengel A. Fuzzy Subjective Sentiment Phrases: A Context Sensitive and Self-Maintaining Sentiment Lexicon. In: Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), IEEE Computer Society; 2014 Aug 1. p. 361-368.
  • Anandan B, Clifton C, Jiang W, Murugesan M, Pastrana-Camacho P, Si L. t-Plausibility: Generalizing Words to Desensitize Text. Transactions on Data Privacy. 2012 Dec; 5(3):505-534.
  • Nguyen-Son HQ, Nguyen QB, Tran MT, Nguyen DT, Yoshiura H, Echizen I. Automatic anonymization of natural languages texts posted on social networking services and automatic detection of disclosure. In: Availability, Reliability and Security (ARES), 2012 Seventh International Conference; 2012 Aug. p. 358-364.
  • Kataoka H, Watanabe N, Mizutani K, Yoshiura H. DCNL: Disclosure Control of Natural Language Information to Enable Secure and Enjoyable E-Communications. In: U-and E-Service, Science and Technology; 2009 Dec. p. 131-140.
  • Shyamala CK, Hemaashri S, Swetha R. An improved recommendation system for social networks. In: International Journal of Control Theory and Applications. (ICSCS). IJCT A International Science Press. 2015; 8(5):1903-1910.


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