A channel state information based virtual MAC spoofing detector
Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
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| Series: | High-Confidence Computing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667295222000198 |
| _version_ | 1828149399512940544 |
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| author | Peng Jiang Hongyi Wu Chunsheng Xin |
| author_facet | Peng Jiang Hongyi Wu Chunsheng Xin |
| author_sort | Peng Jiang |
| collection | DOAJ |
| description | Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. A deep convolutional neural network is constructed to analyze signal level information extracted from Channel State Information (CSI) between the communication peers to provide additional authentication protection at the physical layer. A significant merit of the proposed detection system is that this system can distinguish two different devices even at the same location, which was not well addressed by the existing approaches. Our extensive experimental results demonstrate the effectiveness of the system with an average detection accuracy of 95%, even when devices are co-located. |
| first_indexed | 2024-04-11T21:28:44Z |
| format | Article |
| id | doaj.art-a6d0cd5d1e4647efa8665ccfade54213 |
| institution | Directory Open Access Journal |
| issn | 2667-2952 |
| language | English |
| last_indexed | 2024-04-11T21:28:44Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | High-Confidence Computing |
| spelling | doaj.art-a6d0cd5d1e4647efa8665ccfade542132022-12-22T04:02:16ZengElsevierHigh-Confidence Computing2667-29522022-09-0123100067A channel state information based virtual MAC spoofing detectorPeng Jiang0Hongyi Wu1Chunsheng Xin2Department of ECE, Old Dominion University, Norfolk, VA, USA; School of Cybersecurity, Old Dominion University, Norfolk, VA, USADepartment of ECE, Old Dominion University, Norfolk, VA, USA; School of Cybersecurity, Old Dominion University, Norfolk, VA, USADepartment of ECE, Old Dominion University, Norfolk, VA, USA; School of Cybersecurity, Old Dominion University, Norfolk, VA, USA; Corresponding author.Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. A deep convolutional neural network is constructed to analyze signal level information extracted from Channel State Information (CSI) between the communication peers to provide additional authentication protection at the physical layer. A significant merit of the proposed detection system is that this system can distinguish two different devices even at the same location, which was not well addressed by the existing approaches. Our extensive experimental results demonstrate the effectiveness of the system with an average detection accuracy of 95%, even when devices are co-located.http://www.sciencedirect.com/science/article/pii/S266729522200019800-0199-00 |
| spellingShingle | Peng Jiang Hongyi Wu Chunsheng Xin A channel state information based virtual MAC spoofing detector High-Confidence Computing 00-01 99-00 |
| title | A channel state information based virtual MAC spoofing detector |
| title_full | A channel state information based virtual MAC spoofing detector |
| title_fullStr | A channel state information based virtual MAC spoofing detector |
| title_full_unstemmed | A channel state information based virtual MAC spoofing detector |
| title_short | A channel state information based virtual MAC spoofing detector |
| title_sort | channel state information based virtual mac spoofing detector |
| topic | 00-01 99-00 |
| url | http://www.sciencedirect.com/science/article/pii/S2667295222000198 |
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