PDF
Full
Outline
With the continuous development of mobile communication technologies in intelligent autonomous driving systems，securing vehicular communication data has become pivotal for transportation safety. Faced with threats of hackers remotely manipulating vehicles through the CAN bus network，existing frameworks can detect known attacks but falter in identifying location-based attacks. A detection framework integrating evidence-based deep learning is proposed in this paper，comprising data preprocessing，analysis，and attack detection modules. The preprocessing module employs independent hot encoding to enhance data quality and adaptability. The analysis module utilizes Generative Adversarial Networks （GANs） to bolster the framework's generalization and simulate attack scenarios. The attack detection module harnesses evidence-based deep learning to enhance the framework's capability in handling uncertainties from unknown attacks.The framework is tested on an open-source car hacking dataset and a dataset constructed based on the Chery EXEED RX model. The test results show that the framework improves the overall performance by 24.5% in detecting unknown attacks compared to traditional classification probability-based networks.
PDF
351
158
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
