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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]

From the past few years, Intrusion Detection Systems (IDS) are employed as a second line of defence and have shown to be a useful tool for enhancing security by detecting suspicious activity. Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. Convent...

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Main Authors: Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi
Format: Article
Language:English
Published: UiTM Cawangan Perlis 2022
Subjects:
Software protection
Algorithms
Online Access:https://ir.uitm.edu.my/id/eprint/60675/1/60675.pdf
https://ir.uitm.edu.my/id/eprint/60675/
https://crinn.conferencehunter.com/
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id my.uitm.ir.60675
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spelling my.uitm.ir.606752022-06-16T01:44:38Z https://ir.uitm.edu.my/id/eprint/60675/ An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] Rastogi, Sarthak Shrotriya, Archit Singh, Mitul Kumar Potukuchi, Raghu Vamsi Software protection Algorithms From the past few years, Intrusion Detection Systems (IDS) are employed as a second line of defence and have shown to be a useful tool for enhancing security by detecting suspicious activity. Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. Conventional IDS are less accurate in detecting anomalies because of the decision taking based on rules. The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. The findings reveal which method performed better in terms of accuracy and running time. UiTM Cawangan Perlis 2022 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/60675/1/60675.pdf An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]. (2022) Journal of Computing Research and Innovation (JCRINN), 7 (1): 11. pp. 124-137. ISSN 2600-8793 https://crinn.conferencehunter.com/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Software protection
Algorithms
spellingShingle Software protection
Algorithms
Rastogi, Sarthak
Shrotriya, Archit
Singh, Mitul Kumar
Potukuchi, Raghu Vamsi
An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
description From the past few years, Intrusion Detection Systems (IDS) are employed as a second line of defence and have shown to be a useful tool for enhancing security by detecting suspicious activity. Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. Conventional IDS are less accurate in detecting anomalies because of the decision taking based on rules. The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. The findings reveal which method performed better in terms of accuracy and running time.
format Article
author Rastogi, Sarthak
Shrotriya, Archit
Singh, Mitul Kumar
Potukuchi, Raghu Vamsi
author_facet Rastogi, Sarthak
Shrotriya, Archit
Singh, Mitul Kumar
Potukuchi, Raghu Vamsi
author_sort Rastogi, Sarthak
title An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
title_short An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
title_full An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
title_fullStr An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
title_full_unstemmed An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
title_sort analysis of intrusion detection classification using supervised machine learning algorithms on nsl-kdd dataset / sarthak rastogi ... [et al.]
publisher UiTM Cawangan Perlis
publishDate 2022
url https://ir.uitm.edu.my/id/eprint/60675/1/60675.pdf
https://ir.uitm.edu.my/id/eprint/60675/
https://crinn.conferencehunter.com/
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score 13.211869

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