A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET

Yogesh  Raju Thakre; Aditya Ghadge; Vittal Kale; Harshal Doshi; Prof. Laxman Pawar

A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET

May 2023

Vol-9, Issue-3

Paper ID: 20604

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Intrusion detection Pattern Based Intrusion Detection Intrusion Detection using Statistics.

Abstract

The research paper proposes an intrusion detection method called Incremental Learning and FSVMIL-FSVM, aim-ing to address the limitations of traditional network intrusion detection algorithms in terms of high learning time cost and low recognition accuracy for large-scale training data. The field of networking has experienced significant growth in recent decades, leading to increased threats to computer networks from attackers and hackers. To detect such attacks, an Intrusion Detection System (IDS) is used. The paper introduces a new algorithm, Genetic Algorithm using machine learning, to improve accuracy and speed in detecting network intrusions. The rapid growth of network data and the emergence of various intrusion types highlight the need for effective intrusion detection methods.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Yogesh Raju Thakre	Sinhgad College of Engineering Pune
2	Aditya Ghadge	Sinhgad College of Engineering Pune
3	Vittal Kale	Sinhgad College of Engineering Pune
4	Harshal Doshi	Sinhgad College of Engineering Pune
5	Prof. Laxman Pawar	Sinhgad College of Engineering Pune

How to Cite

Use the following formats to cite this article in your research.

APA Style

Thakre, Yogesh Raju, Ghadge, Aditya, Kale, Vittal, Doshi, Harshal, & Pawar, Prof. Laxman (2023). A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET. International Journal of Advance Research and Innovative Ideas In Education, 9(3), 3097-3101.

MLA Style

Thakre, Yogesh Raju, et al. "A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 3, 2023, pp. 3097-3101.

IEEE Style

Yogesh Raju Thakre, Aditya Ghadge, Vittal Kale, Harshal Doshi, and Prof. Laxman Pawar, "A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 3, pp. 3097-3101, 2023.

Vancouver Style

Thakre Yogesh Raju, Ghadge Aditya, Kale Vittal, Doshi Harshal, Pawar Prof. Laxman. A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(3):3097-3101.

Harvard Style

Thakre, Yogesh Raju, Ghadge, Aditya, Kale, Vittal, Doshi, Harshal, & Pawar, Prof. Laxman (2023) 'A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET', International Journal of Advance Research and Innovative Ideas In Education, 9(3), pp. 3097-3101.

Chicago Style

Thakre, Yogesh Raju, et al. "A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET." International Journal of Advance Research and Innovative Ideas In Education 9, no. 3 (2023): 3097-3101.

Turabian Style

Thakre, Yogesh Raju, et al. "A MACHINE LEARNING APPROACH FOR INTRUSION DETECTION FOR NETWORK DATASET." International Journal of Advance Research and Innovative Ideas In Education 9, no. 3 (2023): 3097-3101.