Botnet Forensic Analysis Using Machine Learning

Author

Bijalwan, Anchit

Source

Security and Communication Networks

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-02-20

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Information Technology and Computer Science

Abstract EN

Botnet forensic analysis helps in understanding the nature of attacks and the modus operandi used by the attackers.

Botnet attacks are difficult to trace because of their rapid pace, epidemic nature, and smaller size.

Machine learning works as a panacea for botnet attack related issues.

It not only facilitates detection but also helps in prevention from bot attack.

The proposed inquisition model endeavors improved quality of results by comprehensive botnet detection and forensic analysis.

This scenario has been applied in eight different combinations of ensemble classifier technique to detect botnet evidence.

The study is also compared to the ensemble-based classifiers with the single classifier using different parameters.

The results exhibit that the proposed model can improve accuracy over a single classifier.

American Psychological Association (APA)

Bijalwan, Anchit. 2020. Botnet Forensic Analysis Using Machine Learning. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1208913

Modern Language Association (MLA)

Bijalwan, Anchit. Botnet Forensic Analysis Using Machine Learning. Security and Communication Networks No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1208913

American Medical Association (AMA)

Bijalwan, Anchit. Botnet Forensic Analysis Using Machine Learning. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1208913

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1208913