A machine learning approach for web intrusion detection

MAMLS perspective

Rajagopal Smitha, K. S. Hareesha, Poornima Panduranga Kundapur

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Open Web Applications Security Project (OWASP), an open-source community committed to serve application developers and security professionals has always accentuated on the dire consequences of web application vulnerabilities like SQLI, XSS, LDAP, and Buffer overflow attacks frequently occurring on the web application threat landscape. Since these attacks are difficult to comprehend, machine learning algorithms are often applied to this problem context for decoding anomalous patterns. This work explores the performance of algorithms like decision forest, neural networks, support vector machine, and logistic regression. Their performance has been evaluated using standard performance metrics. HTTP CSIC 2010, a web intrusion detection dataset is used in this study. Experimental results indicate that SVM and LR have been superior in their performance than their counterparts. Predictive workflows have been created using Microsoft Azure Machine Learning Studio (MAMLS), a scalable machine learning platform which facilitates an integrated development environment to data scientists.

Original languageEnglish
Title of host publicationSoft Computing and Signal Processing - Proceedings of ICSCSP 2018
EditorsV. Kamakshi Prasad, G. Ram Mohana Reddy, Jiacun Wang, V. Sivakumar Reddy
PublisherSpringer Verlag
Pages119-133
Number of pages15
ISBN (Print)9789811335990
DOIs
Publication statusPublished - 01-01-2019
EventInternational Conference on Soft Computing and Signal Processing, ICSCSP 2018 - Hyderabad, India
Duration: 22-06-201823-06-2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume900
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Soft Computing and Signal Processing, ICSCSP 2018
CountryIndia
CityHyderabad
Period22-06-1823-06-18

Fingerprint

Studios
Intrusion detection
Learning systems
HTTP
World Wide Web
Learning algorithms
Support vector machines
Decoding
Logistics
Neural networks

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Smitha, R., Hareesha, K. S., & Kundapur, P. P. (2019). A machine learning approach for web intrusion detection: MAMLS perspective. In V. K. Prasad, G. R. M. Reddy, J. Wang, & V. S. Reddy (Eds.), Soft Computing and Signal Processing - Proceedings of ICSCSP 2018 (pp. 119-133). (Advances in Intelligent Systems and Computing; Vol. 900). Springer Verlag. https://doi.org/10.1007/978-981-13-3600-3_12
Smitha, Rajagopal ; Hareesha, K. S. ; Kundapur, Poornima Panduranga. / A machine learning approach for web intrusion detection : MAMLS perspective. Soft Computing and Signal Processing - Proceedings of ICSCSP 2018. editor / V. Kamakshi Prasad ; G. Ram Mohana Reddy ; Jiacun Wang ; V. Sivakumar Reddy. Springer Verlag, 2019. pp. 119-133 (Advances in Intelligent Systems and Computing).
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Smitha, R, Hareesha, KS & Kundapur, PP 2019, A machine learning approach for web intrusion detection: MAMLS perspective. in VK Prasad, GRM Reddy, J Wang & VS Reddy (eds), Soft Computing and Signal Processing - Proceedings of ICSCSP 2018. Advances in Intelligent Systems and Computing, vol. 900, Springer Verlag, pp. 119-133, International Conference on Soft Computing and Signal Processing, ICSCSP 2018, Hyderabad, India, 22-06-18. https://doi.org/10.1007/978-981-13-3600-3_12

A machine learning approach for web intrusion detection : MAMLS perspective. / Smitha, Rajagopal; Hareesha, K. S.; Kundapur, Poornima Panduranga.

Soft Computing and Signal Processing - Proceedings of ICSCSP 2018. ed. / V. Kamakshi Prasad; G. Ram Mohana Reddy; Jiacun Wang; V. Sivakumar Reddy. Springer Verlag, 2019. p. 119-133 (Advances in Intelligent Systems and Computing; Vol. 900).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Smitha R, Hareesha KS, Kundapur PP. A machine learning approach for web intrusion detection: MAMLS perspective. In Prasad VK, Reddy GRM, Wang J, Reddy VS, editors, Soft Computing and Signal Processing - Proceedings of ICSCSP 2018. Springer Verlag. 2019. p. 119-133. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-13-3600-3_12