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While the convergence of Artificial Intelligence (AI) techniques with improved information technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it also introduced an increased amount of security and…

The Internet of Vehicles (IoV) is transforming transportation by enhancing connectivity and enabling autonomous driving. However, this increased interconnectivity introduces new security vulnerabilities. Bot malware and cyberattacks pose…

Federated learning is a technique of decentralized machine learning. that allows multiple parties to collaborate and learn a shared model without sharing their raw data. Our paper proposes a federated learning framework for intrusion…

Internet of Vehicles (IoVs) consist of smart vehicles, Autonomous Vehicles (AVs) as well as roadside units (RSUs) that communicate wirelessly to provide enhanced transportation services such as improved traffic efficiency and reduced…

This paper aims to propose a novel framework to address the data privacy issue for Federated Learning (FL)-based Intrusion Detection Systems (IDSs) in Internet-of-Vehicles(IoVs) with limited computational resources. In particular, in…

Machine Learning (ML) models are applied in a variety of tasks such as network intrusion detection or Malware classification. Yet, these models are vulnerable to a class of malicious inputs known as adversarial examples. These are slightly…

The Internet of Vehicles (IoV) is a crucial technology for Intelligent Transportation Systems (ITS) that integrates vehicles with the Internet and other entities. The emergence of 5G and the forthcoming 6G networks presents an enormous…

The use of autonomous vehicles (AVs) is a promising technology in Intelligent Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything (V2X) technology enables communication among vehicles and other…

The integration of machine learning (ML) algorithms into Internet of Things (IoT) applications has introduced significant advantages alongside vulnerabilities to adversarial attacks, especially within IoT-based intrusion detection systems…

The Internet of Vehicles (IoV) network can address the issue of limited computing resources and data processing capabilities of individual vehicles, but it also brings the risk of privacy leakage to vehicle users. Applying blockchain…

The Internet of Vehicles (IoV) is flourishing and offers various applications relating to road safety, traffic and fuel efficiency, and infotainment. Dealing with security and privacy threats and managing the trust (detecting malicious and…

Modern vehicles, including autonomous vehicles and connected vehicles, are increasingly connected to the external world, which enables various functionalities and services. However, the improving connectivity also increases the attack…

In Internet of Vehicles (IoV), data sharing among vehicles is essential to improve driving safety and enhance vehicular services. To ensure data sharing security and traceability, highefficiency Delegated Proof-of-Stake consensus scheme as…

Modern vehicles, including autonomous vehicles and connected vehicles, have adopted an increasing variety of functionalities through connections and communications with other vehicles, smart devices, and infrastructures. However, the…

The continuous strengthening of the security posture of IoT ecosystems is vital due to the increasing number of interconnected devices and the volume of sensitive data shared. The utilisation of Machine Learning (ML) capabilities in the…

With rapid technological growth, security attacks are drastically increasing. In many crucial Internet-of-Things (IoT) applications such as healthcare and defense, the early detection of security attacks plays a significant role in…

Device fingerprinting combined with Machine and Deep Learning (ML/DL) report promising performance when detecting cyberattacks targeting data managed by resource-constrained spectrum sensors. However, the amount of data needed to train…

The rapid increase of the data scale in Internet of Vehicles (IoV) system paradigm, hews out new possibilities in boosting the service quality for the emerging applications through data sharing. Nevertheless, privacy concerns are major…

Connected and Autonomous Vehicles (CAVs) enhance mobility but face cybersecurity threats, particularly through the insecure Controller Area Network (CAN) bus. Cyberattacks can have devastating consequences in connected vehicles, including…

The rapid advancement of machine learning (ML) and on-device computing has revolutionized various industries, including transportation, through the development of Connected and Autonomous Vehicles (CAVs) and Intelligent Transportation…