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Detection and Mitigation of DDoS Attack using Machine Learning

Author(s):

Maitri Bharat Dharasandia , D.Y. PATIL COLLEGE OF ENGINEERING & TECHNOLOGY, KASABA BAWADA, KOLHAPUR; Sanyogita Maruti Desai, D.Y. PATIL COLLEGE OF ENGINEERING & TECHNOLOGY, KASABA BAWADA, KOLHAPUR; Pratiksha Baburao Chougule, D.Y. PATIL COLLEGE OF ENGINEERING & TECHNOLOGY, KASABA BAWADA, KOLHAPUR; Mahima Mahesh Sawant, D.Y. PATIL COLLEGE OF ENGINEERING & TECHNOLOGY, KASABA BAWADA, KOLHAPUR

Keywords:

DDoS, Bot, HTTP Requests, Machine Learning

Abstract

One of the major threat to the network security is Distributed Denial of Service attacks. Many company servers have been the victims of this attacks. In a short span of time, these attacks can easily drain the computing resources and services of the victim. Threat of DDoS attack that attempts to make a machine or network resource unavailable is getting serious. In recent years, DDoS attacks have been directed especially towards the application layer. This is increasing mainly due to the large number of existing tools for the generation of this type of attack. HTTP DoS attack is one of the DDoS attack methods that targets HTTP servers. For the evaluation, a large dataset passed to a classification algorithm which detects the source of malicious requests and stops it automatically.

Other Details

Paper ID: IJSRDV8I10330
Published in: Volume : 8, Issue : 1
Publication Date: 01/04/2020
Page(s): 248-249

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