• Sneha Joshi
• Dr. Anitha Patil
• Prof. Srijita Bhattacharjee

A continuous increase in the usage of internet has now resulted in an important topic of research in network traffic analysis domain. Due to the growth in the internet traffic, the complexity in the network botnet detection has increased. It has become a progressively crucial task to understand the behavioral patterns of the users who use various net services and network applications. The proposed system presents a unique approach for botnet detection in the internet traffic. This approach is supported by the behavioral graph analysis to check the similarity in the behavior of hosts. The proposed system uses bipartite graphs to model host communications from network traffic. This is followed by building one mode projections of supported bipartite communication graphs. The one mode projection helps to analyze the similarity in the social-behavior communication of end-hosts. The system uses the economical bunch algorithms on the similarity matrices and grouping related to one-mode projection graphs. It performs network awareness on the group of end hosts within the same network prefixes. The proposed system demonstrates results based mostly on real datasets and shows that end-host and application behavior clusters provide distinct traffic options that proves to improve the interpretations of the internet traffic. It demonstrates the sensible edges of exploring behavior similarity in identification of the network behavior, discovering botnets in the network applications, and sleuthing abnormal traffic patterns.

Networking, Distributed Denial-of-Service, Botnet, DDoS, Cyber security, Signal Processing for Network Security

"BOTNET DETECTION BASED ON BIPARTITE GRAPH AND ONE MODE PROJECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.151-162, July-2018, Available :http://www.jetir.org/papers/JETIR1807622.pdf

"BOTNET DETECTION BASED ON BIPARTITE GRAPH AND ONE MODE PROJECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp151-162, July-2018, Available at : http://www.jetir.org/papers/JETIR1807622.pdf