相关论文: Using Data Analytics to Detect Anomalous States in…

Currently, there are computer vision systems that help us with tasks that would be dull for humans, such as surveillance and vehicle tracking. An important part of this analysis is to identify traffic anomalies. An anomaly tells us that…

The cybersecurity of connected cars, integral to the broader Internet of Things (IoT) landscape, has become of paramount concern. Cyber-attacks, including hijacking and spoofing, pose significant threats to these technological advancements,…

Autonomous vehicles (AV) are becoming a part of humans' everyday life. There are numerous pilot projects of driverless public buses; some car manufacturers deliver their premium-level automobiles with advanced self-driving features. Thus,…

Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/communications. Intrusion Detection Systems (IDS) are widely deployed for anomaly detection in such critical infrastructures. This…

Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, the increasing complexity and connectivity of AV systems introduce significant cybersecurity…

We address the problem of detecting an anomalous process among a large number of processes. At each time t, normal processes are in state zero (normal state), while the abnormal process may be in either state zero (normal state) or state…

Modern vehicles rely on scores of electronic control units (ECUs) broadcasting messages over a few controller area networks (CANs). Bereft of security features, in-vehicle CANs are exposed to cyber manipulation and multiple researches have…

The authors present a cyber-physical systems study on the estimation of driver behavior in autonomous vehicles and vehicle safety systems. Extending upon previous work, the approach described is suitable for the long term estimation and…

Connected Vehicles network is designed to provide a secure and private method for drivers to use the most efficiently the roads in certain area. When dealing with the scenario of car to access points connectivity (Wi-Fi, 3G, LTE), the…

Using Infrastructure-to-Vehicle (I2V) information can be of great benefit when driving autonomously in high-density traffic situations with limited visibility, since the sensing capabilities of the vehicle are enhanced by external sensors.…

Multiple attacks have shown that in-vehicle networks have vulnerabilities which can be exploited. Securing the Controller Area Network (CAN) for modern vehicles has become a necessary task for car manufacturers. Some attacks inject…

Already today, driver assistance systems help to make daily traffic more comfortable and safer. However, there are still situations that are quite rare but are hard to handle at the same time. In order to cope with these situations and to…

Traffic scene analysis is important for emerging technologies such as smart traffic management and autonomous vehicles. However, such analysis also poses potential privacy threats. For example, a system that can recognize license plates may…

Connected vehicles (CVs), because of the external connectivity with other CVs and connected infrastructure, are vulnerable to cyberattacks that can instantly compromise the safety of the vehicle itself and other connected vehicles and…

This thesis addresses the use of Cooperative Intelligent Transport Systems (CITS) to improve road safety and efficiency by enabling vehicle-to-vehicle communication, highlighting the importance of secure and accurate data exchange. To…

Human drivers can recognise fast abnormal driving situations to avoid accidents. Similar to humans, automated vehicles are supposed to perform anomaly detection. In this work, we propose the spatio-temporal graph auto-encoder for learning…

There is an increase in interest to model driving maneuver patterns via the automatic unsupervised clustering of naturalistic sequential kinematic driving data. The patterns learned are often used in transportation research areas such as…

The evolution of Intelligent Transportation System in recent times necessitates the development of self-driving agents: the self-awareness consciousness. This paper aims to introduce a novel method to detect abnormalities based on internal…

In recent years, state-of-the-art traffic-control devices have evolved from standalone hardware to networked smart devices. Smart traffic control enables operators to decrease traffic congestion and environmental impact by acquiring…

In the realm of Cyber-Physical System (CPS), accurately identifying attacks without detailed knowledge of the system's parameters remains a major challenge. When it comes to Advanced Driver Assistance Systems (ADAS), identifying the…