The recent advancement of the Internet of Things (IoT) in the fields of smart vehicles and integration empowers all cars to join to the internet and transfer sensitive traffic information. To enhance the security for the Internet of Vehicles (IoV) and maintain privacy, this paper proposes an ultralight authentication scheme. Physical unclonable function (PUF), supervised machine learning (SML), and XOR functions are used to authenticate both server and device in a two message flow. The proposed framework can authenticate devices with a low computation time (3 ms) compared to other proposed frameworks while protecting against existing potential threats. Furthermore, the proposed framework needs low overhead (21 bytes) that avoids adding to the IoV network’s workload. Moreover, SML makes weak PUF responses as random numbers to provide the functionality of a strong PUF for the framework. In addition, both formal (Burrows, Abadi, Needham (BAN) logic) and informal analysis are presented to show the resistance against known attacks.
The Internet of things (IoT) presents unique challenges for the deployment of machine learning (ML) models, particularly due to constraints on computational resources, the necessity for decentralized processing, and concerns regarding security and privacy in interconnected enviro…
This research work highlights significant achievements in the domain of intrusion detection systems (IDSs) for autonomous vehicles, which are crucial in enhancing their safety, reliability, and cybersecurity. This study introduces an approach that leverages non-tree-based machine…
The rapid deployment of electric vehicle (EV) charging infrastructure, coupled with the integration of 5G/6G and Internet of Vehicles (IoV) technologies, has transformed charging stations into cyber–physical systems that rely on wireless communication for authentication, control,…
This paper presents a machine learning-based approach to grade engine health and generate a respective score ranging from 0 to 100 for tuned high-performance vehicles. It integrates the technical intricacies of automotive engineering with machine learning practices in a clear and…
In-vehicle networks (IVNs) are networks that allow communication between different electronic components in a vehicle, such as infotainment systems, sensors, and control units. As these networks become more complex and interconnected, they become more vulnerable to cyber-attacks…
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the method…