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Published in:

Volume 8 Issue 2
February-2021
eISSN: 2349-5162

Unique Identifier

JETIR2102033

Page Number

315-319

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Title

A Survey on HTTP BotNet Detection Techniques using Machine Learning

ISSN

2349-5162

Cite This Article

"A Survey on HTTP BotNet Detection Techniques using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 2, page no.315-319, February-2021, Available :http://www.jetir.org/papers/JETIR2102033.pdf

Abstract

A botnet is a group of computers linked to the Internet which have been compromised and are being controlled remotely by the botmaster through malicious software called bots. While substantial research work has been accomplished on botnet analysis and detection, many challenges remain unaddressed, such as the ability to design detectors that can cope with new forms of botnets. So there is a need for an advanced system that can detect traffic behavior accurately. This paper provides the state-of-art techniques used by the researchers for the detection of a botnet attack.

Key Words

A Survey on HTTP BotNet Detection Techniques using Machine Learning

Cite This Article

"A Survey on HTTP BotNet Detection Techniques using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 2, page no. pp315-319, February-2021, Available at : http://www.jetir.org/papers/JETIR2102033.pdf

Publication Details

Published Paper ID: JETIR2102033
Registration ID: 305452
Published In: Volume 8 | Issue 2 | Year February-2021
DOI (Digital Object Identifier):
Page No: 315-319
ISSN Number: 2349-5162

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Cite This Article

"A Survey on HTTP BotNet Detection Techniques using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 2, page no. pp315-319, February-2021, Available at : http://www.jetir.org/papers/JETIR2102033.pdf




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