Back to Search
Start Over
Enhancing IoT security in wireless local area networks through dynamic vulnerability scanning.
Enhancing IoT security in wireless local area networks through dynamic vulnerability scanning.
- Source :
-
Sādhanā: Academy Proceedings in Engineering Sciences . Sep2024, Vol. 49 Issue 3, p1-19. 19p. - Publication Year :
- 2024
-
Abstract
- Wireless local area networks (WLANs) play a crucial role in the internet of things (IoT) landscape, facilitating constant data exchange among devices. However, the inherent security vulnerabilities in these networks, stemming from limited computational resources, pose significant challenges to deploying robust security measures. This research addresses the security concerns surrounding IoT devices within the IEEE 802.11ah WLAN environment by introducing the SecureScanML algorithm, a novel machine learning (ML) approach designed to optimize Internet-wide port scans (IWPS) for enhanced device security while preserving network performance. The SecureScanML algorithm leverages Q-learning, a reinforcement learning technique, to dynamically adjust the scan rates of IoT devices adaptively. Through this approach, the algorithm effectively reduces vulnerabilities, achieving a notable 35.7% reduction, while maintaining key network performance metrics. With a throughput of 2.8 Mbps, a packet delivery ratio of 97.3%, an adaptability index of 0.91, a convergence speed of 420 s, and a low latency of 42 ms, the proposed algorithm surpasses existing methods such as TA, RA, SSR, CNN-LSTM, RLA, and RSR. Simulation results corroborate the efficacy of SecureScanML in mitigating vulnerabilities without compromising network efficiency. The algorithm strikes a fine balance between proactive vulnerability management and network performance preservation. Moreover, the study explores the impact of security-performance weight parameters on the algorithm's behavior, providing valuable insights for fine-tuning the system to achieve specific security and performance objectives. Notably, for a security-performance weight of 0.5, the algorithm demonstrates high throughput and vulnerability reduction alongside low latency. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02562499
- Volume :
- 49
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Sādhanā: Academy Proceedings in Engineering Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 178527536
- Full Text :
- https://doi.org/10.1007/s12046-024-02534-8