The week's pick
Random Articles
Reseach Article
A Novel Approach for Secure Hidden Community Mining in Social Networks using Data Mining Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 87 - Number 7 |
| Year of Publication: 2014 |
| Authors: R. Renuga Devi, M. Hemalatha |
10.5120/15219-3728
|
R. Renuga Devi, M. Hemalatha . A Novel Approach for Secure Hidden Community Mining in Social Networks using Data Mining Techniques. International Journal of Computer Applications. 87, 7 ( February 2014), 12-19. DOI=10.5120/15219-3728
Abstract
Social network community contains a group of nodes connected on the basis of certain relationships or same properties. Sometimes it refers to the special kind of network arrangement where the Community Mining discovers all communities hidden in distributed networks based on their important similarities. Different methods and algorithms have been employed to carry out the task of community mining. Conversely, in the real world, many applications entail distributed and dynamically evolving networks. This leads a problem of finding all communities from a given network. Detecting evolutionary communities in these networks can help the user for better understanding the structural evolution of the networks. In this research, first a new bipartisan scheme using k- Dimensional (KD) –Tree to deal with the recursive bisection method is proposed; next an Improved KD-Tree algorithm to deal with the multidimensional problem is put forward. The security issue such as a Sybil attack (Multiple fake Identities attack) arises in these network structures. It can be mitigated by fixing the target time by using SICTF (Sybil Identification using Connectivity Threshold and Frequency of visit) algorithm. The problem faced by the mining community of heterogeneous network can be addressed by using Convergence aware Dirichlet Process Mixture Model (CADPM).
References
- Yang, B. , Liu, J. , and Feng, J. 2012. On the spectral characterization and scalable mining of network communities. Knowledge and Data Engineering, IEEE Transactions On, 24(2), 326-337.
- Tang, L. , Liu, H. , Zhang, J. , and Nazeri, Z. 2008. Community evolution in dynamic multi-mode networks. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM. 677-685.
- Yu, H. , Kaminsky, M. , Gibbons, P. B. , and Flaxman, A. 2006. Sybilguard: defending against Sybil attacks via social networks. ACM SIGCOMM Computer Communication Review, 36 (4), 267-278.
- Yu, H. , Gibbons, P. B. , Kaminsky, M. , and Xiao, F. 2008. Sybillimit: A near-optimal social network defense against Sybil attacks. In Security and Privacy, 2008. SP 2008. IEEE Symposium on IEEE. 3-17.
- Tran, D. N. , Min, B. , Li, J. , & Subramanian, L. (2009, April). Sybil-Resilient Online Content Voting. In NSDI. 9(1): 15-28.
- Walsh, K. , and Sirer, E. G. 2006. Experience with an object reputation system for peer-to-peer file sharing. NSDI. Proceedings of the 3rd conference on 3rd Symposium on Networked Systems Design & Implementation.
- Peterson, R. , and Sirer, E. G. 2009. AntFarm: Efficient Content Distribution with Managed Swarms. In NSDI. 9(1): 107-122.
- Piatek, M. , Isdal, T. , Krishnamurthy, A. , and Anderson, T. E. 2008. One Hop Reputations for Peer to Peer File Sharing Workloads. In NSDI. 8(1): 1-14.
- Cai, D. , Shao, Z. , He, X. , Yan, X. , and Han, J. 2005. Mining hidden community in heterogeneous social networks. In Proceedings of the 3rd international workshop on Link discovery. ACM. 58-65.
- Newman, M. E. , and Girvan, M. 2004. Finding and evaluating community structure in networks. Physical review E, 69(2), 026113.
- Newman, M. E. 2006. Finding community structure in networks using the eigenvectors of matrices. Physical review E, 74(3), 036104.
- Sun, Yizhou, and Jiawei Han, 2010. Integrating Clustering with Ranking in Heterogeneous Information Networks Analysis. Link Mining: Models, Algorithms, and Applications. Springer New York, 439-473.
- Sun, Y. , Yu, Y. , and Han, J. 2009. Ranking-based clustering of heterogeneous information networks with star network schema. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM. 797-806.
- Xu, T. , Zhang, Z. , Yu, P. S. , and Long, B. 2008. Dirichlet process based evolutionary clustering. In Data Mining, 2008. ICDM'08. Eighth International Conference on IEEE. 648-657.
- Xu, T. , Zhang, Z. , Yu, P. S. , & Long, B. 2008. Evolutionary clustering by a hierarchical Dirichlet process with the hidden Markov state. In Data Mining, 2008. ICDM'08. Eighth International Conference on IEEE. 658-667.
- Sun, Y. , Tang, J. , Han, J. , Gupta, M. , and Zhao, B. 2010. Community evolution detection in dynamic heterogeneous information networks. In Proceedings of the Eighth Workshop on Mining and Learning with Graphs. ACM. 137-146.
Index Terms
Keywords