CVPD: A tool based on a social network analysis to combating viruses propagation

It has been seen that Social network analysis is gaining its applicability in several areas like business, marketing, biology, disease modeling, and anti-terrorism. In this paper, we have discussed its practical application in the domain of computer network to identify distribution of computer viruses flowing through the network. To the best of our knowledge this is a novel idea and is based on the gSpan (Graph based substructure Pattern Mining) algorithm for identifying frequent pattern of viruses flowing in a particular region of connected nodes. This crusades make analysist enabled to deal with the problems and deploy more efficient antivirus in that region of nodes.

[1]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[2]  Mason A. Porter,et al.  Communities in Networks , 2009, ArXiv.

[3]  Tom A. B. Snijders,et al.  Social Network Analysis , 2011, International Encyclopedia of Statistical Science.

[4]  B. Wellman Computer Networks As Social Networks , 2001, Science.

[5]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[6]  R. Hanneman Introduction to Social Network Methods , 2001 .

[7]  Jiawei Han,et al.  gSpan: graph-based substructure pattern mining , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[8]  George Karypis,et al.  Finding Frequent Patterns in a Large Sparse Graph* , 2005, Data Mining and Knowledge Discovery.