A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks
Software-defined vehicles (SDVs) make automotive systems more intelligent and adaptable, and this transformation relies on hybrid automotive in-vehicle networks that refer to multiple protocols using automotive Ethernet (AE) or a controller area network (CAN). Numerous researchers have developed spe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/13/7/1317 |
| _version_ | 1797212678446383104 |
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| author | Shanshan Wang Hainan Zhou Haihang Zhao Yi Wang Anyu Cheng Jin Wu |
| author_facet | Shanshan Wang Hainan Zhou Haihang Zhao Yi Wang Anyu Cheng Jin Wu |
| author_sort | Shanshan Wang |
| collection | DOAJ |
| description | Software-defined vehicles (SDVs) make automotive systems more intelligent and adaptable, and this transformation relies on hybrid automotive in-vehicle networks that refer to multiple protocols using automotive Ethernet (AE) or a controller area network (CAN). Numerous researchers have developed specific intrusion-detection systems (IDSs) based on ResNet18, VGG16, and Inception for AE or CANs, to improve confidentiality and integrity. Although these IDSs can be extended to hybrid automotive in-vehicle networks, these methods often overlook the requirements of real-time processing and minimizing of the false positive rate (FPR), which can lead to safety and reliability issues. Therefore, we introduced an IDS based on the Swin Transformer to bolster hybrid automotive in-vehicle network reliability and security. First, multiple messages from the traffic assembly are transformed into images and compressed via two-dimensional wavelet discrete transform (2D DWT) to minimize parameters. Second, the Swin Transformer is deployed to extract spatial and sequential features to identify anomalous patterns with its attention mechanism. To compare fairly, we re-implemented up-to-date conventional network models, including ResNet18, VGG16, and Inception. The results showed that our method could detect attacks with 99.82% accuracy and 0 FPR, which saved 14.32% in time costs and improved the accuracy by 1.60% compared to VGG16 when processing 512 messages. |
| first_indexed | 2024-04-24T10:46:12Z |
| format | Article |
| id | doaj.art-046fa0fa516548edac97f388cf8d516c |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-04-24T10:46:12Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-046fa0fa516548edac97f388cf8d516c2024-04-12T13:17:22ZengMDPI AGElectronics2079-92922024-03-01137131710.3390/electronics13071317A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle NetworksShanshan Wang0Hainan Zhou1Haihang Zhao2Yi Wang3Anyu Cheng4Jin Wu5School of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaProduct Cybersecurity & Privacy Office, Continental Automotive Singapore, Singapore 339780, SingaporeSchool of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSchool of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaSoftware-defined vehicles (SDVs) make automotive systems more intelligent and adaptable, and this transformation relies on hybrid automotive in-vehicle networks that refer to multiple protocols using automotive Ethernet (AE) or a controller area network (CAN). Numerous researchers have developed specific intrusion-detection systems (IDSs) based on ResNet18, VGG16, and Inception for AE or CANs, to improve confidentiality and integrity. Although these IDSs can be extended to hybrid automotive in-vehicle networks, these methods often overlook the requirements of real-time processing and minimizing of the false positive rate (FPR), which can lead to safety and reliability issues. Therefore, we introduced an IDS based on the Swin Transformer to bolster hybrid automotive in-vehicle network reliability and security. First, multiple messages from the traffic assembly are transformed into images and compressed via two-dimensional wavelet discrete transform (2D DWT) to minimize parameters. Second, the Swin Transformer is deployed to extract spatial and sequential features to identify anomalous patterns with its attention mechanism. To compare fairly, we re-implemented up-to-date conventional network models, including ResNet18, VGG16, and Inception. The results showed that our method could detect attacks with 99.82% accuracy and 0 FPR, which saved 14.32% in time costs and improved the accuracy by 1.60% compared to VGG16 when processing 512 messages.https://www.mdpi.com/2079-9292/13/7/1317hybrid automotive in-vehicle networkIDSAECANSwin Transformer2D DWT |
| spellingShingle | Shanshan Wang Hainan Zhou Haihang Zhao Yi Wang Anyu Cheng Jin Wu A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks Electronics hybrid automotive in-vehicle network IDS AE CAN Swin Transformer 2D DWT |
| title | A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks |
| title_full | A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks |
| title_fullStr | A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks |
| title_full_unstemmed | A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks |
| title_short | A Zero False Positive Rate of IDS Based on Swin Transformer for Hybrid Automotive In-Vehicle Networks |
| title_sort | zero false positive rate of ids based on swin transformer for hybrid automotive in vehicle networks |
| topic | hybrid automotive in-vehicle network IDS AE CAN Swin Transformer 2D DWT |
| url | https://www.mdpi.com/2079-9292/13/7/1317 |
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