Randomised Traffic Path Analysis and Formation For Detecting Distributed Denial of Service Botnet Attacks
M. Maheswari1, Madhana Gopal Bhavani2, Tanya Aggarwal3

Manuscript received on 02 July 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 27 August 2019 | PP: 128-130 | Volume-8 Issue-2S4 July 2019 | Retrieval Number: B10230782S419/2019©BEIESP | DOI: 10.35940/ijrte.B1023.0782S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Botnets are most commonly used in cyber- criminal activity. They’re used for spamming, phishing, denial-of-service attacks, stealing non-public data, and cyber warfare. A botnet may be a range of net computers that, though their homeowners are unaware of but have gotten wind of, forward transmissions (including spam or viruses) to alternative computers on the web. There is a two-stage approach for botnet detection. The primary stage detects and collects network anomalies that are related to the presence of a botnet whereas the second stage identifies the bots by analyzing these anomalies.
Keywords: Intrusion, Coarse Grained, Botnet, DDOS.
Scope of the Article: Predictive Analysis