AI-enabled security mechanisms for WLANs: ensuring robust and adaptive protection in wireless networks
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2025
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| _version_ | 1866902197716910080 |
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| author | Sachan, Ram Chandra Lakhani, Rishit Poddar, Sanjay |
| author_facet | Sachan, Ram Chandra Lakhani, Rishit Poddar, Sanjay |
| contents | <p>Wireless Local Area Networks (WLANs) have become important to current digital infrastructures, linking various devices and enabling smooth data transmission. However, their ubiquity makes them attractive targets for cybercriminals, who constantly look for imaginative techniques to access wireless networks. With its predictive, adaptive, and very responsive defense, artificial intelligence (AI) presents a potent weapon for enhancing WLAN security. Examining how machine learning models detect and minimize risks with unheard-of speed and accuracy, this paper investigates the possibilities of AI-enabled security measures. Different approaches—including autonomous decision-making and real-time data analysis—are explored to show how artificial intelligence might find zero-day exploits and advanced cyberattacks. Furthermore, illuminating effective practices for strong wireless defense are important results from literature and pragmatic uses. The paper ends by stressing the possibilities and difficulties of including artificial intelligence in WLAN security and outlining future directions. </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17192238 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI-enabled security mechanisms for WLANs: ensuring robust and adaptive protection in wireless networks Sachan, Ram Chandra Lakhani, Rishit Poddar, Sanjay Wireless Security Ai Defense Threat Detection Anomaly Analysis Network Protection Adaptive Encryption <p>Wireless Local Area Networks (WLANs) have become important to current digital infrastructures, linking various devices and enabling smooth data transmission. However, their ubiquity makes them attractive targets for cybercriminals, who constantly look for imaginative techniques to access wireless networks. With its predictive, adaptive, and very responsive defense, artificial intelligence (AI) presents a potent weapon for enhancing WLAN security. Examining how machine learning models detect and minimize risks with unheard-of speed and accuracy, this paper investigates the possibilities of AI-enabled security measures. Different approaches—including autonomous decision-making and real-time data analysis—are explored to show how artificial intelligence might find zero-day exploits and advanced cyberattacks. Furthermore, illuminating effective practices for strong wireless defense are important results from literature and pragmatic uses. The paper ends by stressing the possibilities and difficulties of including artificial intelligence in WLAN security and outlining future directions. </p> |
| title | AI-enabled security mechanisms for WLANs: ensuring robust and adaptive protection in wireless networks |
| topic | Wireless Security Ai Defense Threat Detection Anomaly Analysis Network Protection Adaptive Encryption |
| url | https://doi.org/10.5281/zenodo.17192238 |