Entropy of Network Analysis and Cluster Detection Using Markov Theory

Authors

  • N Siranjeevi Assistant Professor, Department of Computer Science, AVS College of Arts and Science, Salem, Tamil Nadu, India
  • P. Priya Assistant Professor, Department of Computer Science, AVS College of Arts and Science, Salem, Tamil Nadu, India
  • S. Thangavelu Assistant Professor, Department of Computer Science, AVS College of Arts and Science, Salem, Tamil Nadu, India

Keywords:

Markov matrix, entropy network

Abstract

Networks square measure an important part of nature and society; nonetheless several aspects of networks operate square measure still mostly unknown. from understanding the networks play a task; however even a small number of the foremost basic questions about networks will be troublesome to answer. Nevertheless, square measure two networks alike or different? However, do networks within networks type and the way will clusters be detected? As networks have amendment with time, nevertheless will we have a tendency to monitor those changes? The answers to those queries square measure vitally necessary to humans’ understanding of the planet. Higher understanding of networks permits for things like a lot of economical electrical distribution grids and a lot of reliable period of time network intrusion detection systems. It conjointly permits for a more robust understanding of nevertheless nature type’s networks just like the bonds that form molecules and therefore the networks that carry water from the mountains to the ocean and back once more.

Cite this Article

Siranjeevi N, Priya P, Thangavelu S. Entropy of Network Analysis and Cluster Detection Using Markov Theory. Journal of Network Security. 2018; 6(3): 1–4p

References

Vladimir Estivill-Castro. Why So Many Clustering Algorithms: A Position Paper. ACM SIGKDD Explorations Newsletter. Jun 2002; 4: 65–75p.

Emily Singer. Natural Networks, Strength in Loops. Quanta Magazine; Aug 2013.

Brett Meador. A Survey of Computer Network Topology and Analysis Examples. Nov 2008.

Sitabhra Sinha. Physics of Complex Networks. Proceedings of the DAE Solid State Physics Symposium. 2007.

Suratna Budalakoti. Anomaly Detection Using Hierarchical Hidden Markov Models. University of California, Santa Cruz.

Santo Fortunato. Community Detection in Graphs. Complex Networks and Systems Lagrange Laboratory.

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Published

2019-02-04

Issue

Vol. 6 No. 3 (2018)

Section

Research Articles

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