A survey on misbehavior detection for connected and autonomous vehicles
Connected and autonomous vehicles have recently emerged as promising technological
solutions to optimize traffic congestion, prevent accidents, and enhance driving safety and …
solutions to optimize traffic congestion, prevent accidents, and enhance driving safety and …
A machine-learning-based data-centric misbehavior detection model for internet of vehicles
P Sharma, H Liu - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) boosts road safety, efficiency, and infotainment by connecting
vehicles to form the Internet of Vehicles (IoV). Specifically to safety, IoV complements …
vehicles to form the Internet of Vehicles (IoV). Specifically to safety, IoV complements …
Attacks on machine learning: Adversarial examples in connected and autonomous vehicles
P Sharma, D Austin, H Liu - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Connected and autonomous vehicles (CAV aka driverless cars) offset human response for
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …
Real-time adaptive sensor attack detection in autonomous cyber-physical systems
Cyber-Physical Systems (CPS) tightly couple information technology with physical
processes, which rises new vulnerabilities such as physical attacks that are beyond …
processes, which rises new vulnerabilities such as physical attacks that are beyond …
Physical invariant based attack detection for autonomous vehicles: Survey, vision, and challenges
Automobiles continue to become more autonomous and connected as increasingly
integrating with information technology. Meanwhile, this advance also comes with a higher …
integrating with information technology. Meanwhile, this advance also comes with a higher …
[HTML][HTML] Machine learning-based imputation approach with dynamic feature extraction for wireless RAN performance data preprocessing
JNM Dahj, KA Ogudo - Symmetry, 2023 - mdpi.com
Machine learning (ML) in wireless mobile communication is becoming more and more
customary, with application trends leaning toward performance improvement and network …
customary, with application trends leaning toward performance improvement and network …
Detecting can masquerade attacks with signal clustering similarity
Vehicular Controller Area Networks (CANs) are susceptible to cyber attacks of different
levels of sophistication. Fabrication attacks are the easiest to administer--an adversary …
levels of sophistication. Fabrication attacks are the easiest to administer--an adversary …
[PDF][PDF] Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking.
Recent advancements in the Vehicular Ad-hoc Network (VANET) have tremendously
addressed road-related challenges. Specifically, Named Data Networking (NDN) in VANET …
addressed road-related challenges. Specifically, Named Data Networking (NDN) in VANET …
GenVRAM: Dataset Generator for Vehicle to Roadside Attacks and Misbehavior
D Ramsamooj, P Sharma, H Liu - IEEE Access, 2024 - ieeexplore.ieee.org
The surge in the number of driverless cars highlights the necessity for enhanced
transportation safety and efficiency. Achieving fully autonomous driving depends on the …
transportation safety and efficiency. Achieving fully autonomous driving depends on the …
Adversarial Attack Detection for Deep Learning Driving Maneuver Classifiers in Connected Autonomous Vehicles
Connected and autonomous vehicles (CAVs) will be equipped with onboard deep neural
network (DNN) models for processing the data from different sensors and communication …
network (DNN) models for processing the data from different sensors and communication …