Intrusion Detection System for IoT-based Healthcare Intrusions with Lion-Salp-Swarm-Optimization Algorithm: Metaheuristic-Enabled Hybrid Intelligent Approach

Nidhi Goswami1

Sahil Raj1

Deepti Thakral2

José Luis Arias-Gonzáles3

Judith Flores-Albornoz4

Edwin Asnate-Salazar5

Dhiraj Kapila6

Sanjay Yadav7

Surendra Kumar8,Email

1Department of Computer science and Engineering, Sanskriti University, Mathura, India.
2Department of Computer Science and Technology, Manav Rachna University, Faridabad, India.
3University of British Columbia, Columbia.
4Universidad Nacional Santiago Antúnez de Mayolo, Huaraz, Peru.
5Department of CSE, Universidad Nacional Santiago Antunez de Mayolo, Huaraz, Peru.
6Department of CSE, Lovely Professional University, Phagwara, Punjab, India.
7Department of Computer science Koneru Lakshmaaiah education foundation vaddeswaram Guntur A.P.
8Department of Computer Engineering and Applications, GLA University, Mathura, India.

Abstract

The Internet of Things (IoT) makes IoT devices more vulnerable to cyberattacks, especially Distributed Denial of Service (DDoS), raising privacy and security issues. Application-layer DDoS: zombie machines submit queries to the affected server. IDS cannot detect these requests because TCP connections are valid. In this research, we propose the Lion-Salp-Swarm-Optimization Algorithm (LSSOA), which utilizes the freely available IoT-Flock software to create a dataset containing both legitimate and malicious traffic. We employ metaheuristic algorithms like Lion optimization, Whale optimization, Spider-Monkey optimization, and Salp Swarm optimization to detect online attacks and defend the Internet of Medical Things (IoMT) environment. Our framework accurately detects attacks while reducing false positives by overcoming intrusion detection restrictions. Our metaheuristic algorithm outperforms others. Our method is useful for Internet of Things-based enterprises. Overall, the LSSOA framework provides a powerful tool to detect and prevent cyber-attacks in the IoMT environment, demonstrating the potential benefits of novel intrusion detection techniques. Our study emphasizes the importance of enhancing IoT security, particularly in critical industries like healthcare, and highlights the need for continuous efforts to develop effective and innovative approaches to address emerging cyber threats.

Intrusion Detection System for IoT-based Healthcare Intrusions with Lion-Salp-Swarm-Optimization Algorithm: Metaheuristic-Enabled Hybrid Intelligent Approach