相关论文: Detecting Masquerade Attacks in Controller Area Ne…

The automotive market is increasingly profitable for cyberattacks with the constant shift toward fully interconnected vehicles. Electronic Control Units (ECUs) installed on cars often operate in a critical and hostile environment. Hence,…

The emerging paradigm of Quantum Machine Learning (QML) combines features of quantum computing and machine learning (ML). QML enables the generation and recognition of statistical data patterns that classical computers and classical ML…

Today's vehicles are complex distributed embedded systems that are increasingly being connected to various external systems. Unfortunately, this increased connectivity makes the vehicles vulnerable to security attacks that can be…

With the benefits of Internet of Vehicles (IoV) paradigm, come along unprecedented security challenges. Among many applications of inter-connected systems, vehicular networks and smart cars are examples that are already rolled out. Smart…

Modern traffic management systems increasingly adopt hierarchical control strategies for improved efficiency and scalability, where a local traffic controller mode is chosen by a supervisory controller based on the changing large-scale…

Complex electronic control unit (ECU) architectures, software models and in-vehicle networks are consistently improving safety and comfort functions in modern vehicles. However, the extended functionality and increased connectivity…

Complex interconnections between information technology and digital control systems have significantly increased cybersecurity vulnerabilities in smart grids. Cyberattacks involving data integrity can be very disruptive because of their…

In a spoofing attack, a malicious actor impersonates a legitimate user to access or manipulate data without authorization. The vulnerability of cryptographic security mechanisms to compromised user credentials motivates spoofing attack…

Graph modeling allows numerous security problems to be tackled in a general way, however, little work has been done to understand their ability to withstand adversarial attacks. We design and evaluate two novel graph attacks against a…

Mobile Crowdsensing systems are vulnerable to various attacks as they build on non-dedicated and ubiquitous properties. Machine learning (ML)-based approaches are widely investigated to build attack detection systems and ensure MCS systems…

Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary solution to the problem. In this work, we present a novel framework that detects…

Malware detection has become a major concern due to the increasing number and complexity of malware. Traditional detection methods based on signatures and heuristics are used for malware detection, but unfortunately, they suffer from poor…

Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML)…

Recent advances in Machine Learning (ML) have shown a great potential to build data-driven solutions for a plethora of network-related problems. In this context, building fast and accurate network models is essential to achieve functional…

The CAN Bus is crucial to the efficiency, and safety of modern vehicle infrastructure. Electronic Control Units (ECUs) exchange data across a shared bus, dropping messages whenever errors occur. If an ECU generates enough errors, their…

Modern vehicles are complex safety critical cyber physical systems, that are connected to the outside world, with all security implications that brings. To enhance vehicle security several network intrusion detection systems (NIDS) have…

Most of the intrusion detection methods in computer networks are based on traffic flow characteristics. However, this approach may not fully exploit the potential of deep learning algorithms to directly extract features and patterns from…

While emerging adaptive cruise control (ACC) technologies are making their way into more vehicles, they also expose a vulnerability to potential malicious cyberattacks. Previous research has typically focused on constant or stochastic…

The Internet of Vehicles (IoV) is advancing modern transportation by improving safety, efficiency, and intelligence. However, the reliance on the Controller Area Network (CAN) introduces critical security risks, as CAN-based communication…

Recent experimental studies have shown that traffic management systems are vulnerable to cyber-attacks on sensor data. This paper studies the vulnerability of fixed-time control of signalized intersections when sensors measuring traffic…