• Sayalee Mahendra Patil
• SWARDHA SAWANT
• CHINMAY RAUT

Cyber crime is increasing in our day to day lives. Various type of cyber attacks like phishing attacks, ransomware attacks and DDOS attacks are increasing tremendously at a higher attack. The threat of cyber attack is increasing nowadays in the technology driven world. In the DDoS attack hackers generally send a large number of requests to the targeted websites which will then exceed the capacity of the website ultimately impairing their ability to function normally. This attack cannot be prevented but one can detect this DDOS attack. In this project “Detectors” we are implementing the types of DDOS attack using various best algorithms which are having highest accuracy for detecting, so after testing for various algorithm we have selected for decision tree algorithm for classifying normal or an attacker class. When user will give the input for the type of attack he/she wants to test the system will give accurate results.

DDOS attack detection , Decision tree , Logistic regression , MLP , DDoS , Machine learning

"DDOS ATTACK DETECTION USING ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.b157-b161, April-2022, Available :http://www.jetir.org/papers/JETIR2204120.pdf

"DDOS ATTACK DETECTION USING ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppb157-b161, April-2022, Available at : http://www.jetir.org/papers/JETIR2204120.pdf