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Detection and Analysis of Hidden Activities in Social Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 77 - Number 16 |
| Year of Publication: 2013 |
| Authors: Divya Prakash, Subu Surendran |
10.5120/13570-1404
|
Divya Prakash, Subu Surendran . Detection and Analysis of Hidden Activities in Social Networks. International Journal of Computer Applications. 77, 16 ( September 2013), 34-38. DOI=10.5120/13570-1404
Abstract
Social networks are flourishing because of fast growing Internet and the World Wide Web, and more research efforts have been put on Social Network Analysis (SNA). A social network can be modeled like a graph, where the nodes represent persons, and an edge between them represent direct relationship between the persons. One of the issues in SNA is to identifying criminals from groups of individuals. In a real social network, there must have various relationships between individuals, like friendships, business relationships, and common interest relationships etc. The internet itself is a huge social network. To model such a network, link analysis need to be proposed. A page in web may treat as a node, and hyperlink between them can be represented as relationships. After social network graph is constructed, link analysis and graph partitioning algorithms may be applied to identify the hidden links in that network. Most of the existing algorithms related to social network analysis assume that their existing only one single social network, with relatively multiple relationship like Web page linkage. In typical social networks, there always have various kinds of relations. Every relation can be identified as a relation network. These different types of relations play different tasks in different roles. The work here attempts to find the problem of mining hidden relationships on social networks. Social network analysis (SNA) is a set of powerful techniques that can be used to identify clusters, patterns and hidden structures within social networks. Here the problem is identified with the following steps. 1. Analyzing information flow through the network using affected dataset, 2. Discovering non-obvious relations between actors, and 3. Identifying nodes that are directly or indirectly connected to most other nodes in the social network. This is done with the help of mining algorithms like Min-cut and Regression.
References
- G. Aggarwal, T. Feder, K. Kenthapadi, Samir Khuller, R. Panigrahy, D. Thomas, and A. Zhu, "Achieving Anonymity via Clustering," Proceedings of PODS, June 26-28, Chicago, Illinois, US, 2006.
- Z. Baird, J. Barksdale, and M. Vatis, "Creating a Trusted Network for Homeland Security", Markle Foundation, 2003.
- Z. Baird and J. Barksdale, "Mobilizing Information to Prevent Terrorism: Accelerating Development of a Trusted Information Sharing Environment", Markle Foundation, 2006.
- C. Best, J. Piskorski, B. Pouliquen, R. Steinberger and H. Tanev, "Chapter 2. Automating Event Extraction for the Security Domain, Intelligence and Security Informatics: Applications and Technique", Editors: H. Chen and C. C. Yang, Springer-Verlag, to appear in 2008.
- . Caruson, S. A. Macmanus, M. Khoen, and T. A. Watson, "Homeland Security Preparedness: The Rebirth of Regionalism," Publius, 35(1), 2005, pp. 143-189.
- R. R. Friedmann and W. J. Cannon, "Homeland Security and Community Policing: Competing or Complementing Public Safety Policies," Journal of Homeland Security and Emergency Management, 4(4), 2005, pp. 1-20.
- Arquilla, J. , Ronfeld, D. : "Networks and Netwars: The Future of Terror, Crime, and Militancy". RAND Corporation, Santa Monica, CA (2001)
- Xuning Tang and Christopher C. Yang, " Terrorist and Criminal Social Network Data Sharing and Integration," College of Information Science and Technology Drexel University, Philadelphia 2009.
- K. Liu and E. Terzi, "Towards Identity Anonymization on Graphs," in ACM SIGMOD'08 Vancouver, BC, Canada: ACM Press, 2008.
- C. C. Yang, "Information Sharing and Privacy Protection of Terrorist or Criminal Social Networks," Proceeding of IEEE International Conference on Intelligence and Security Informatics, Taipei, Taiwan, 2008.
- B. Zhou and J. Pei, "Preserving Privacy in Social Networks against Neighborhood Attacks," in IEEE International Conference on Data Engineering, 2008.
- D. Thacher, "The Local Role in Homeland Security," Law &Society, 39(3), 2005, pp. 557-570.
- B. Thuraisingham, "Security Issues for Federated Databases Systems," Computers and Security, North Holland, December,1994.
- B. Thuraisingham, "Chapter 1. Assured Information Sharing:Technologies: Challenges and Directions, Intelligence and Security Informatics: Applications and Technique", Editors:H. Chen and C. C. Yang, Springer-Verlag, to appear in 2008.
- R. C. Wong, J. Li, A. Fu, and K. Wang, "k-Anonymity: An Enhanced k-Anonymity Model for Privacy-Preserving Data Publishing," Proceedings of SIGKDD, August 20-23, Philadelphia, Pennsylvania, US, 2006.
- X. Xiao and Y. Tao, "Personalized Privacy Preservation, "Proceedings of SIGMOD, June 27-29, Chicago, Illinois, 2006.
- C. C. Yang, N. Liu, and M. Sageman, "Analyzing the Terrorist Social Networks with Visualization Tools," Proceedings of the IEEE International Conference on Intelligence and Security Informatics, San Diego, CA, US, May 23 – 24, 2006.
- C. C. Yang and T. D. Ng, "Terrorism and Crime Related Weblog Social Network: Link, Content Analysis and Information Visualization," Proceedings of the IEEE International Conference on Intelligence and Security Informatics, New Brunswick, New Jersey, May 23-24, 2007.
- D. Cai, Z. Shao, X. He, X. Yan, and J. Han. "Mining hidden community in heterogeneous social networks. Technical report", Computer Science Department,UIUC, UIUCDCS-R-2005-2538, May, 2005.
- Nasrullah M, Henrik L, D. M. Akbar Hussain, "Constructing Hierarchy of Non-hierarchical Terrorist Networks, Study from Theory to Implementation for Analyzing and Destabilizing Terrorist Networks", DCMMC - 2006, Washington DC,USA, September 28 – 29 2006.
- Newman M. E. J. ; "A measure of betweenness centrality based on random walks", cond-mat/0309045,2003.
- Latora V, Marchiori M. ; "A measure of centrality based on network efficiency", arxiv. org preprint condmat/0402050, 2004.
- J. J. Xu, and H. Chen, "Untangling Criminal Networks: A Case Study", ISI 2003 pp. 232-248, 2003.
- R. V. Hauck, H. Atabakhsh, P. Ongvasith, H. Gupta, H. Chen, Using Coplink to analyze criminal-justice data. IEEE Computer, Vol. 35, No. 3: 3037, 2002.
- J. M. McGloin et al. , "Investigating the stability of cooffending and co-offenders among a sample of youthful offenders Criminology", 2008.
- A. J. Reiss, "Co-offending and criminal careers, Crime and Justice: A Review of Research", IEEE 1988.
- Hsinchun Chen Michael Chau,Shu-hsing Li Shalini Urs,Srinath Srinivasa G. Alan Wang(Eds. ), "Intelligence and Security Informatics",Springer Verlag Berlin Heidelberg 2010.
- Xiaowei Ying , Xintao Wu ; Barbara, D. ,"Spectrum based fraud detection in social networks",, IEEE 27th International Conference on Data Engineering (ICDE),2011,Page 912 – 923.
- Abhishek Sachan, Devshri Roy, "TGPM: Terrorist Group Prediction Model for Counter Terrorism",International Journal of Computer Applications (0975 – 8887) Volume 44– No10, April 2012.
- Tayebi, M. A. ,Glasser U," Organized Crime Structures in Co-offending Networks ",IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing (DASC), 2011,Pages 846 – 853.
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