The automobile industry no longer relies on pure mechanical systems; instead, it benefits from many smart features based on advanced embedded electronics. Although the rise in electronics and connectivity has improved comfort, functionality, and safe driving, it has also created new attack surfaces to penetrate the in-vehicle communication network, which was initially designed as a close loop system. For such applications, the Controller Area Network (CAN) is the most-widely used communication protocol, which still suffers from various security issues because of the lack of encryption and authentication. As a result, any malicious/hijacked node can cause catastrophic accidents and financial loss. This paper analyses the CAN bus comprehensively to provide an outlook on security concerns. It also presents the security vulnerabilities of the CAN and a state-of-the-art attack surface with cases of implemented attack scenarios and goes through different solutions that assist in attack prevention, mainly based on an intrusion detection system (IDS).

The vehicles are equipped with electronic control units that control their functions. These units communicate with each other via in-vehicle communication protocols like CAN bus. Although CAN is the most common in-vehicle communication protocol, its lack of encryption and authentication can cause serious security shortcomings. In the literature, many attacks are reported related to CAN bus and the number increases with rising connectivity in the cars. In this paper, we present CAN protocol and analyze its security vulnerabilities. Then we survey the implemented attacks and proposed solutions in the literature.

Vehicles are equipped with Electronic Control Units (ECUs) to increase their overall system functionality and connectivity. However, the rising connectivity exposes a defenseless internal Controller Area Network (CAN) to cyberattacks. An Intrusion Detection System (IDS) is a supervisory module, proposed for identifying CAN network malicious messages, without modifying legacy ECUs and causing high traffic overhead. The traditional IDS approaches rely on time and frequency thresholding, leading to high false alarm rates, whereas state-of-the-art solutions may suffer from vehicle dependency. This paper presents a wavelet-based approach to locating the behavior change in the CAN traffic by analyzing the CAN network's transmission pattern. The proposed Wavelet-based Intrusion Detection System (WINDS) is tested on various attack scenarios, using real vehicle traffic from two independent research centers, while being expanded toward more comprehensive attack scenarios using synthetic attacks. The technique is evaluated and compared against the state-of-the-art solutions and the baseline frequency method. Experimental results show that WINDS offers a vehicle-independent solution applicable for various vehicles through a unique approach while generating low false alarms.

Modern energy systems face increasing operational challenges due to the growing penetration of renewables, variability in generation and network congestion, which contribute to curtailment, inefficiencies and avoidable emissions. These issues constrain system flexibility and hinder progress towards net‐zero targets. Digitalisation offers a means to address these challenges by improving system observability, enabling real‐time coordination and supporting data‐driven decision‐making through technologies such as the Internet of Things, artificial intelligence and digital twin. As a result, digitalisation has enhanced the efficiency, reliability and flexibility of energy systems, supporting progress towards net‐zero emissions targets. This paper reviews key technologies that enable energy system digitalisation and examines challenges arising from increased connectivity. Unlike existing studies that consider individual technologies, market mechanisms or policy frameworks in isolation, this work adopts an integrated perspective encompassing enabling technologies, data‐driven applications, data governance and cyber security within digitalised energy systems. This study is guided by a horizon scanning methodology to identify emerging technological and cyber‐physical challenges shaping future energy system design. Additionally, a six‐dimensional framework for energy data governance is used to structure current practices and identify gaps related to data quality, discoverability, sharing, privacy and emerging responsibilities. This paper offers actionable insights for researchers, policymakers and industry stakeholders while identifying areas that require further technical and regulatory development.

In this paper, a layered security mechanism for IEEE 1687 is proposed using a new class of physically unclonable function (PUF) called Bimodal PUF. It moves beyond the conventional single-challenge single-response PUF by introducing a second response to the PUF gained from the same single challenge. As an advantage, a double-response PUF forms two-layer security solution, one at the hardware layer by limiting the access to the embedded instrument and the second one for the data layer by securing the output data that needs to be transmitted. Experiments conducted with FPGA show that such advantages come in place at a small silicon area overhead, up to 1.4%, for a 64-bit security key. This is known to be sufficient enough to resist brute-force and machine learning attack.