Detection of DoS Attacks Using Machine Learning Based Intrusion Detection System
- Title
- Detection of DoS Attacks Using Machine Learning Based Intrusion Detection System
- Creator
- Sabu I.R.; Saju S.; Mary Anita E.A.; Sowmya T.
- Description
- Conventional intrusion detection systems are not always sufficient due to the increasing sophistication and frequency of Denial-of-Service (DoS) attacks. This work presents a novel solution to this problem by leveraging machine learning techniques to increase the precision and efficacy of real-time intrusion detection. The system keeps a careful eye on network traffic patterns, looking for any irregularities that would point to a denial-of-service attack. An Intrusion Detection System (IDS) that utilizes machine learning technologies - specifically, neural networks and support vector machines - allows for real-time adaptation to new attack patterns. A combination of rigorous simulations and real-world testing provides empirical support for the IDS's quick detection and mitigation of DoS threats. This initiative makes a major contribution to the development of cybersecurity defenses. 2024 IEEE.
- Source
- Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- DoS Attacks; Intrusion Detection System; Machine learning; Support Vector Machine (SVM)
- Coverage
- Sabu I.R., CHRIST (Deemed to be University), Computer Science and Engineering, Bangalore, India; Saju S., CHRIST (Deemed to be University), Computer Science and Engineering, Bangalore, India; Mary Anita E.A., CHRIST (Deemed to be University), Computer Science and Engineering, Bangalore, India; Sowmya T., CHRIST (Deemed to be University), Computer Science and Engineering, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038365-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sabu I.R.; Saju S.; Mary Anita E.A.; Sowmya T., “Detection of DoS Attacks Using Machine Learning Based Intrusion Detection System,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19233.