AI-Based Intrusion Detection Techniques for Vehicle Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 10 October 2025 | Viewed by 358
Special Issue Editor
Interests: artificial intelligence security; blockchain; Intelligent connected vehicle; cryptography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid development of intelligent transportation systems and the increasing connectivity of vehicles have made the in-vehicle network a critical component that enables the exchange of data between various electronic control units (ECUs) and external systems. However, this interconnectivity also exposes vehicles to a wide range of cybersecurity risks. Traditional security measures are often inadequate to defend against sophisticated cyberattacks. This necessitates the development of advanced intrusion detection techniques that can effectively identify and mitigate potential threats.
Artificial intelligence (AI) leverages the power of machine learning, deep learning, and other AI algorithms to indicate potential cyberattacks in in-vehicle networks. AI techniques can continuously learn and adapt to changes in vehicle behavior, improving their ability to detect and mitigate evolving cyber threats.
This Special Issue focuses on AI-based intrusion detection techniques for in-vehicle networks. We welcome research and developments which explore a wide range of topics, including anomaly detection algorithms, supervised and unsupervised learning techniques, deep learning models, and their applications in detecting different types of cyberattacks.
Prof. Dr. Xiangxue Li
Guest Editor
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Keywords
- artificial intelligence
- intrusion detection
- vehicle networks
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