相关论文: Detecting CAN Masquerade Attacks with Signal Clust…

Off-the-shelf software for Command and Control is often used by attackers and legitimate pentesters looking for discretion. Among other functionalities, these tools facilitate the customization of their network traffic so it can mimic…

Connected and autonomous vehicles, also known as CAVs, are a general trend in the evolution of the automotive industry that can be utilized to make transportation safer, improve the number of mobility options available, user costs will go…

Autonomous vehicles (AVs) rely heavily on cameras and artificial intelligence (AI) to make safe and accurate driving decisions. However, since AI is the core enabling technology, this raises serious cyber threats that hinder the large-scale…

Capsule Networks preserve the hierarchical spatial relationships between objects, and thereby bears a potential to surpass the performance of traditional Convolutional Neural Networks (CNNs) in performing tasks like image classification. A…

Machine learning (ML) has established itself as a cornerstone for various critical applications ranging from autonomous driving to authentication systems. However, with this increasing adoption rate of machine learning models, multiple…

By using various sensors to measure the surroundings and sharing local sensor information with the surrounding vehicles through wireless networks, connected and automated vehicles (CAVs) are expected to increase safety, efficiency, and…

Using generative adversarial network (GAN)\cite{RN90} for data enhancement of medical images is significantly helpful for many computer-aided diagnosis (CAD) tasks. A new attack called CT-GAN has emerged. It can inject or remove lung cancer…

Today's Cyber-Physical Systems (CPSs) are large, complex, and affixed with networked sensors and actuators that are targets for cyber-attacks. Conventional detection techniques are unable to deal with the increasingly dynamic and complex…

The automobile industry is no longer relying on pure mechanical systems; instead, it benefits from advanced Electronic Control Units (ECUs) in order to provide new and complex functionalities in the effort to move toward fully connected…

Recent studies have demonstrated that object detection networks are usually vulnerable to adversarial examples. Generally, adversarial attacks for object detection can be categorized into targeted and untargeted attacks. Compared with…

Dozens of Electronic Control Units (ECUs) can be found on modern vehicles for safety and driving assistance. These ECUs also introduce new security vulnerabilities as recent attacks have been reported by plugging the in-vehicle system or…

This study presents an approach to lane detection involving the prediction of binary segmentation masks and per-pixel affinity fields. These affinity fields, along with the binary masks, can then be used to cluster lane pixels horizontally…

Connected and Autonomous Vehicles (CAVs) rely on Vehicular Adhoc Networks with wireless communication between vehicles and roadside infrastructure to support safe operation. However, cybersecurity attacks pose a threat to VANETs and the…

Capsule network is a type of neural network that uses the spatial relationship between features to classify images. By capturing the poses and relative positions between features, its ability to recognize affine transformation is improved,…

Time series analysis has achieved great success in cyber security such as intrusion detection and device identification. Learning similarities among multiple time series is a crucial problem since it serves as the foundation for downstream…

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…

Cooperative Adaptive Cruise Control (CACC) is a technology that allows groups of vehicles to form in automated, tightly-coupled platoons. CACC schemes exploit Vehicle-to-Vehicle (V2V) wireless communications to exchange information between…

Each day, anti-virus companies receive tens of thousands samples of potentially harmful executables. Many of the malicious samples are variations of previously encountered malware, created by their authors to evade pattern-based detection.…

Most autonomous vehicles (AVs) rely on LiDAR and RGB camera sensors for perception. Using these point cloud and image data, perception models based on deep neural nets (DNNs) have achieved state-of-the-art performance in 3D detection. The…

Clustering models constitute a class of unsupervised machine learning methods which are used in a number of application pipelines, and play a vital role in modern data science. With recent advancements in deep learning -- deep clustering…