Related papers: A Multilayered Security Infrastructure for Connect…
While automated vehicles (AVs) are expected to revolutionize future transportation systems, emerging AV technologies open a door for malicious actors to compromise intelligent vehicles. As the first generation of AVs, adaptive cruise…
Defending computer networks from cyber attack requires coordinating actions across multiple nodes based on imperfect indicators of compromise while minimizing disruptions to network operations. Advanced attacks can progress with few…
High-end vehicles have been furnished with a number of electronic control units (ECUs), which provide upgrading functions to enhance the driving experience. The controller area network (CAN) is a well-known protocol that connects these ECUs…
Data from interconnected vehicles may contain sensitive information such as location, driving behavior, personal identifiers, etc. Without adequate safeguards, sharing this data jeopardizes data privacy and system security. The current…
Driverless vehicles are expected to form the foundation of future connected transport infrastructure. A key weakness of connected vehicles is their vulnerability to physical-proximity attacks such as sensor saturation attacks. It is natural…
The Internet of Vehicles (IoV) has evolved modern transportation through enhanced connectivity and intelligent systems. However, this increased connectivity introduces critical vulnerabilities, making vehicles susceptible to cyber-attacks…
Cyber attacks have become a vital threat to connected autonomous vehicles in intelligent transportation systems. Cyber threat intelligence, as the collection of cyber threat information, provides an ideal approach for responding to emerging…
In this paper we present the first safe system for full control of self-driving vehicles trained from human demonstrations and deployed in challenging, real-world, urban environments. Current industry-standard solutions use rule-based…
With the growing interconnection between In-Vehicle Networks (IVNs) and external environments, intelligent vehicles are increasingly vulnerable to sophisticated external network attacks. This paper proposes ATHENA, the first IVN intrusion…
The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computational demands on execution platforms, posing challenges to real-time control deadlines.…
Modern vehicles may contain a considerable number of ECUs (Electronic Control Units) which are connected through various means of communication, with the CAN (Controller Area Network) protocol being the most widely used. However, several…
The connected vehicle (CV) system promises unprecedented safety, mobility, environmental, economic and social benefits, which can be unlocked using the enormous amount of data shared between vehicles and infrastructure (e.g., traffic…
Connected and autonomous vehicles (CAVs) will form the backbone of future next-generation intelligent transportation systems (ITS) providing travel comfort, road safety, along with a number of value-added services. Such a…
The proliferation of connected automated vehicles represents an unprecedented opportunity for improving driving efficiency and alleviating traffic congestion. However, existing research fails to address realistic multi-lane highway…
With the rapid growth of mobile applications and cloud computing, mobile cloud computing has attracted great interest from both academia and industry. However, mobile cloud applications are facing security issues such as data integrity,…
As a rapidly growing cyber-physical platform, Autonomous Vehicles (AVs) are encountering more security challenges as their capabilities continue to expand. In recent years, adversaries are actively targeting the perception sensors of…
We consider a transportation system of heterogeneously connected vehicles, where not all vehicles are able to communicate. Heterogeneous connectivity in transportation systems is coupled to practical constraints such that (i) not all…
In the automotive industry there is a need to handle broad quality deficiencies, eg, performance, maintainability, cybersecurity, safety, and privacy, to mention a few. The idea is to prevent these issues from reaching end-users, ie, road…
Defending computer networks from cyber attack requires timely responses to alerts and threat intelligence. Decisions about how to respond involve coordinating actions across multiple nodes based on imperfect indicators of compromise while…
We present a control approach for autonomous vehicles based on deep reinforcement learning. A neural network agent is trained to map its estimated state to acceleration and steering commands given the objective of reaching a specific target…