Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP)
Rogue Access Points (RAPs) pose a significant security threat by mimicking legitimate Wi-Fi networks and potentially compromising sensitive data. To address this issue, this research has proposed an innovative mechanism called Invisible Scout, which uses a multi-module system to identify RAPs. This...
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Ital Publication
2025-02-01
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| Series: | Emerging Science Journal |
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| Online Access: | https://ijournalse.org/index.php/ESJ/article/view/2723 |
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| author | Diki Arisandi Nazrul M. Ahmad Subarmaniam Kannan |
| author_facet | Diki Arisandi Nazrul M. Ahmad Subarmaniam Kannan |
| author_sort | Diki Arisandi |
| collection | DOAJ |
| description | Rogue Access Points (RAPs) pose a significant security threat by mimicking legitimate Wi-Fi networks and potentially compromising sensitive data. To address this issue, this research has proposed an innovative mechanism called Invisible Scout, which uses a multi-module system to identify RAPs. This study aimed to develop and validate a mechanism capable of accurately detecting RAPs in controlled setups, real-world environments, and under de-authentication attack scenarios. The proposed system consists of four key modules: sniffer, detection, probing, and comparison. To evaluate its effectiveness, tests were conducted in controlled and open environments and under de-authentication scenarios, using decision tree models and various metrics to assess performance. The decision tree model showed promising results in the controlled setup, achieving an Area Under the Curve (AUC) score of 0.921 and classification accuracy (CA) of 0.875, indicating that the model effectively distinguished between legitimate access points and RAPs. When tested in an open environment, the model's performance improved, achieving an AUC score of 0.952 and a CA of 0.994. Furthermore, under a de-authentication attack, the model achieved an AUC score of 0.955 and a CA of 0.996. To gain a deeper understanding of RAP behaviors, linear regression analysis was conducted, revealing patterns and visualizing the existence of RAPs, which could assist in further analysis. In conclusion, the results demonstrated that the proposed mechanism was highly effective in identifying RAPs. Future research should focus on refining the detection mechanism, incorporating real-time response capabilities, and expanding testing to diverse network scenarios.
Doi: 10.28991/ESJ-2025-09-01-016
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| format | Article |
| id | doaj-art-07a672bad7c64ab3b14658554402956d |
| institution | Kabale University |
| issn | 2610-9182 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Ital Publication |
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| series | Emerging Science Journal |
| spelling | doaj-art-07a672bad7c64ab3b14658554402956d2025-02-08T14:26:27ZengItal PublicationEmerging Science Journal2610-91822025-02-019128431010.28991/ESJ-2025-09-01-016776Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP)Diki Arisandi0Nazrul M. Ahmad1Subarmaniam Kannan2Faculty of Information Science and Technology, Multimedia University, Melaka 75450,Faculty of Information Science and Technology, Multimedia University, Melaka 75450,Faculty of Information Science and Technology, Multimedia University, Melaka 75450,Rogue Access Points (RAPs) pose a significant security threat by mimicking legitimate Wi-Fi networks and potentially compromising sensitive data. To address this issue, this research has proposed an innovative mechanism called Invisible Scout, which uses a multi-module system to identify RAPs. This study aimed to develop and validate a mechanism capable of accurately detecting RAPs in controlled setups, real-world environments, and under de-authentication attack scenarios. The proposed system consists of four key modules: sniffer, detection, probing, and comparison. To evaluate its effectiveness, tests were conducted in controlled and open environments and under de-authentication scenarios, using decision tree models and various metrics to assess performance. The decision tree model showed promising results in the controlled setup, achieving an Area Under the Curve (AUC) score of 0.921 and classification accuracy (CA) of 0.875, indicating that the model effectively distinguished between legitimate access points and RAPs. When tested in an open environment, the model's performance improved, achieving an AUC score of 0.952 and a CA of 0.994. Furthermore, under a de-authentication attack, the model achieved an AUC score of 0.955 and a CA of 0.996. To gain a deeper understanding of RAP behaviors, linear regression analysis was conducted, revealing patterns and visualizing the existence of RAPs, which could assist in further analysis. In conclusion, the results demonstrated that the proposed mechanism was highly effective in identifying RAPs. Future research should focus on refining the detection mechanism, incorporating real-time response capabilities, and expanding testing to diverse network scenarios. Doi: 10.28991/ESJ-2025-09-01-016 Full Text: PDFhttps://ijournalse.org/index.php/ESJ/article/view/2723anomalybeacon framesclient-side scenarioinvisible scoutlayer 2rogue access point. |
| spellingShingle | Diki Arisandi Nazrul M. Ahmad Subarmaniam Kannan Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) Emerging Science Journal anomaly beacon frames client-side scenario invisible scout layer 2 rogue access point. |
| title | Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) |
| title_full | Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) |
| title_fullStr | Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) |
| title_full_unstemmed | Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) |
| title_short | Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) |
| title_sort | invisible scout a layer 2 anomaly system for detecting rogue access point rap |
| topic | anomaly beacon frames client-side scenario invisible scout layer 2 rogue access point. |
| url | https://ijournalse.org/index.php/ESJ/article/view/2723 |
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