Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
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Article Number | 01070 | |
Number of page(s) | 6 | |
DOI | https://doi.org/10.1051/e3sconf/202343001070 | |
Published online | 06 October 2023 |
Ensemble Framework of Artificial immune system based on Network Intrusion Detection System for Network Security Sustainability
1 Department of Information Technology, CVR College of Engineering, Hyderabad, Telangana, India
2 Department of CSE, BVRIT HYDERABAD College for Women, Hyderabad, Telangana, India
3 CSE Department, Vidya Jyothi Institute of Technology, Hyderabad, Telangana, India
4 Department, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, India
5 Uttaranchal Institute of Management, Uttaranchal University, Dehradun, India
6 KG Reddy College of Engineering & Technology, Hyderabad, Telangana, India
* Corresponding author: k.sarangam@gmail.com
The popularity and rapid growth of the internet have reemphasized the importance of intrusion detection systems (IDS) significance in the network security. IDS decreases hacking, data theft risk, privacy intrusion, and others. To save the system from external and internal intruders, the primary approaches of IDS are used. Many techniques[13], like genetic algorithms, artificial neural networks, and artificial immune systems, have been applied to IDS. This paper describes an Ensemble Framework of Artificial Immune System (AIS) based on Network Intrusion Detection System. Without placing a significant additional load on networks and monitoring systems, the large volume of data is analysed by a network-based Intrusion Detection System (NIDS). For determining the connection type, data from KDD Cup 99 competitions is utilized. To differentiate between attacks and valid connections, IDS can be utilized. Optimized feature selection is used to speed up the time-consuming rough set. The results obtained from the IDS system indicate that it can effectively identify the attacking connections with a high success rate.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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