CFP last date
22 April 2024
Reseach Article

Comparison of K-automorphism and K2-degree Anonymization for Privacy Preserving in Social Network

by Sumit Kumar Chaurasia, Nishchol Mishra, Sanjeev Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 79 - Number 14
Year of Publication: 2013
Authors: Sumit Kumar Chaurasia, Nishchol Mishra, Sanjeev Sharma
10.5120/13811-1871

Sumit Kumar Chaurasia, Nishchol Mishra, Sanjeev Sharma . Comparison of K-automorphism and K2-degree Anonymization for Privacy Preserving in Social Network. International Journal of Computer Applications. 79, 14 ( October 2013), 30-36. DOI=10.5120/13811-1871

@article{ 10.5120/13811-1871,
author = { Sumit Kumar Chaurasia, Nishchol Mishra, Sanjeev Sharma },
title = { Comparison of K-automorphism and K2-degree Anonymization for Privacy Preserving in Social Network },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 79 },
number = { 14 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 30-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume79/number14/13811-1871/ },
doi = { 10.5120/13811-1871 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:53:00.655418+05:30
%A Sumit Kumar Chaurasia
%A Nishchol Mishra
%A Sanjeev Sharma
%T Comparison of K-automorphism and K2-degree Anonymization for Privacy Preserving in Social Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 79
%N 14
%P 30-36
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Social networking sites are extensively useful for communicating with the real world. The conversation among these sites accomplishes an extreme amount of data in the network. These large amount of data contain vulnerable information that is sharing between social users through links or edges. A broad use of social network creates security and privacy issues of a network. Many of social users unguarded about the risks, which caused by extrovert their sensible data, make network bunce for identity, and link disclosure. Simply the privacy of users is preserve by removing the identified element of users but it is not enough for user's privacy through attacks, which have some prior knowledge about users. This paper mainly concerned with friendship and structural attack on user's privacy, which disclose user's identity and link information. . Detailed analysis is done regarding k2-degree and k-automorphism methods for protecting the privacy from these attacks and the utility such as average shortest path and cluster coefficient were also calculated for these two method.

References
  1. C. C. Aggarwal (Ed. ), social network data analysis, DOI 10. 1007/978-1-4419-8462-3_10, @ Springer Science+Business Media, LLC 2011.
  2. Fard, Amin Milani, Ke Wang, and Philip S. Yu. "Limiting link disclosure in social network analysis through Subgraph-wise perturbation. " In Proceedings of the 15th International Conference on Extending Database Technology, pp. 109-119. ACM, 2012.
  3. Tai, C. H. , Yu, P. S. , Yang, D. N. , & Chen, M. S. (2011, August). Privacy-preserving social network publication against friendship attacks. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 1262-1270). ACM.
  4. Tai, Chih-Hua, S. Yu Philip, De-Nian Yang, and Ming-Syan Chen. "Structural Diversity for Privacy in Publishing Social Networks. " In SDM, pp. 35-46. 2011.
  5. Cheng, James, Ada Wai-chee Fu, and Jia Liu. "K-isomorphism: privacy preserving network publication against structural attacks. " In Proceedings of the 2010 international conference on Management of data, pp. 459-470. ACM, 2010
  6. Zhang, Lijie, and Weining Zhang. "Edge anonymity in social network graphs. " InComputational Science and Engineering, 2009. CSE'09. International Conference on, vol. 4, pp. 1-8. IEEE, 2009
  7. Zou, Lei, Lei Chen, and M. Tamer Özsu. "K-automorphism: A general framework for privacy preserving network publication. " Proceedings of the VLDB Endowment 2. 1 (2009): 946-957.
  8. Hay, Michael, Gerome Miklau, David Jensen, Don Towsley, and Philipp Weis. "Resisting structural re-identification in anonymized social networks. "Proceedings of the VLDB Endowment 1, no. 1 (2008): 102-114.
  9. Korolova, Aleksandra, Rajeev Motwani, Shubha U. Nabar, and Ying Xu. "Link privacy in social networks. " In Proceedings of the 17th ACM conference on Information and knowledge management, pp. 289-298. ACM, 2008.
  10. Liu, Kun, and Evimaria Terzi. "Towards identity anonymization on graphs. " InProceedings of the 2008 ACM SIGMOD international conference on Management of data, pp. 93-106. ACM, 2008.
  11. Zheleva, Elena, and Lise Getoor. "Preserving the privacy of sensitive relationships in graph data. " In Privacy, security, and trust in KDD, pp. 153-171. Springer Berlin Heidelberg, 2008
  12. Zhou, Bin, and Jian Pei. "Preserving privacy in social networks against neighborhood attacks. " In Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on, pp. 506-515. IEEE, 2008.
  13. Machanavajjhala, Ashwin, et al. "l-diversity: Privacy beyond k-anonymity. " ACM Transactions on Knowledge Discovery from Data (TKDD) 1. 1 (2007): 3.
  14. N. , Li, T. , & Venkatasubramanian, S. (2007, April). t-closeness: Privacy beyond k-anonymity and l-diversity. In Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on (pp. 106-115). IEEE
  15. Backstrom, Lars, Dan Huttenlocher, Jon Kleinberg, and Xiangyang Lan. "Group formation in large social networks: membership, growth, and evolution. " InProceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 44-54. ACM, 2006.
  16. Kumar, Ravi, Jasmine Novak, and Andrew Tomkins. "Structure and Evolution of Online Social Networks. " (2006).
  17. Samarati, Pierangela. "Protecting respondents identities in microdata release. "Knowledge and Data Engineering, IEEE Transactions on 13, no. 6 (2001): 1010-1027.
Index Terms

Computer Science
Information Sciences

Keywords

Social network k2-degree k-automorphism Anonymization.