• P.THILAGAVATHI
• Dr.S.J. Sathish Aaron Joseph

Abstract A botnet attack is a large-scale cyber attack carried out by malware-infected devices which are controlled remotely. It turns compromised devices into ‘zombie bots’ for a botnet controller. Unlike other malware that replicates itself within a single machine or system, botnets pose a greater threat because they let a threat actor perform a large number of actions at the same time. Botnet attacks are akin to having a threat actor working within the network, as opposed to a piece of self-replicating malware. The botnet detection plays a crucial role here as they act as an initial step towards the botnet remedy. Different techniques have been proposed by the IT community and cyber security to prevent or escape from the notorious activities of the botnets. But still these techniques are not so good and needs a lot of work to be done in the botnet prevention, detection and mitigation. In this research, I propose an Anomaly based detection techniques to detect botnet attack by analyzing network traffic for anomalies such as traffic on unusual ports, high network latency, large amount of traffic and abnormal system behaviour. I used K means algorithm to classify botnet activities and prophet routing protocol is used to segment the route to detect the botnet attack. They are further categorized into host-based and network-based detection. Results show the ability of the proposed approach to detect botnet activities with high accuracy and performance in a short execution time.

Botnet, Anomaly Based, K-means, prophet

"PREVENTION OF ANOMALY BASED BOTNET ATTACK DETECTION USING K-MEANS ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.a911-a921, September-2022, Available :http://www.jetir.org/papers/JETIR2209097.pdf

"PREVENTION OF ANOMALY BASED BOTNET ATTACK DETECTION USING K-MEANS ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppa911-a921, September-2022, Available at : http://www.jetir.org/papers/JETIR2209097.pdf