• Prof. Chaitali Bhalerao
• Riddhika Kulkarni
• Swapnil Bobade
• Krutika Bharekar
• Vaishnavi Zadbuke

The field of information and computer security is rapidly developing in today’s world number of security risks is continuously being explored every day. Botnet detection is an active area of research as no single technique is available that can detect the botnet attack very efficiently. The paper gives the system that can detect botnet activity based on traffic behavior analysis by classifying network traffic behavior using machine learning. Traffic behavior analysis methods do not depend on the packets payload, which means that they can work with encrypted network communication protocols. Network traffic information can usually be easily retrieved from various network devices without affecting significantly network performance or service availability.

Security, Botnet Activity Detection, Machine learning, Traffic behavior, TCP Packet, TCP Packet Filtering, Feed Forward Neural Network.

"Implementation of HTTP BotNet Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.f358-f365, May-2021, Available :http://www.jetir.org/papers/JETIR2105715.pdf

"Implementation of HTTP BotNet Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppf358-f365, May-2021, Available at : http://www.jetir.org/papers/JETIR2105715.pdf