Heatwaves are defined as unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. This paper investigates: 1) changes in heatwave characteristics such as peak temperature, number of events, frequency and duration over a past 67-year period in Australia; 2) projected changes in heatwave characteristics for this century in Queensland, northeast Australia; and 3) the avoided heatwave impacts of limiting global warming by 1.5 °C, 2.0 °C and 3.0 °C. The results reveal that heatwaves have increased in intensity, frequency and duration across Australia over the past 67 years, such intensification was particularly higher on recent decades. Downscaled future climate projections for Queensland suggest that heatwaves will further intensify over the current century. The projections also highlight that distinct climatic regions within Queensland may have different heatwave responses under global warming, where tropical and equatorial heatwaves appear to be more sensitive to elevated atmospheric CO₂ concentrations than temperate and arid regions. The results offer new insights to support climate adaptation and mitigation at regional scales. These findings are already being used by health and emergency services to inform the development of statewide policies to mitigate heatwave impacts.

High‐resolution climate change projections are increasingly necessary to inform climate policy and adaptation planning. Downscaling of global climate models (GCMs) is required to simulate the climate at the spatial scale relevant for local impacts. Here, we dynamically downscaled 15 CMIP6 GCMs to a 10 km resolution over Australia using the Conformal Cubic Atmospheric model (CCAM), creating the largest ensemble of high‐resolution downscaled CMIP6 projections for Australia. We compared the host CMIP6 models and downscaled simulations to the Australian Gridded Climate Data (AGCD) observational data and evaluated performance using the Kling‐Gupta efficiency and Perkins skill score. Downscaling improved performance over host GCMs for seasonal temperature and precipitation (10% and 43% respectively), and for annual cycles of temperature and precipitation (6% and 13% respectively). Downscaling also improved the fraction of dry days, reducing the bias for too many low‐rain days. The largest improvements were found in climate extremes, with enhancements to extreme minimum temperatures in all seasons varying from 142% to 201%, and to extreme precipitation of 52% in Austral winter and 47% in summer. The ensemble average integrated skill score improved by 16%. Temperature and precipitation biases were reduced in mountainous and coastal areas. CCAM downscaling outperformed host CMIP6 GCMs at multiple spatial scales and regions—continental Australia, Australian IPCC regions and Queensland's regions—with integrated added value ranging from 9% to 150% and higher over densely populated regions more exposed to climate impacts. This data set will be a valuable resource for understanding future climate changes in Australia.

Quantum computing is emerging as a significant threat to information protected by widely used cryptographic systems. Cryptographic methods, once deemed secure for decades, are now at risk of being compromised, posing a massive threat to the security of sensitive data and communications across enterprises worldwide. As a result, there is an urgent need to migrate to quantum-resistant cryptographic systems. This is no simple task. Migrating to a quantum-safe state is a complex process, and many organisations lack the in-house expertise to navigate this transition without guidance. In this paper, we present a comprehensive framework designed to assist enterprises with this migration. Our framework outlines essential steps involved in the cryptographic migration process, and leverages existing organisational inventories. The framework facilitates the efficient identification of cryptographic assets and can be integrated with other enterprise frameworks smoothly. To underscore its practicality and effectiveness, we have incorporated case studies that utilise graph-theoretic techniques to pinpoint and assess cryptographic dependencies. This is useful in prioritising crypto-systems for replacement.

In intelligent vehicular networks, vehicles have enhanced sensing capabilities and carry computing and communication platforms to enable new versatile systems known as Vehicular Communication (VC) systems. Vehicles communicate with other vehicles and with nearby fixed equipment to support different applications, including those which increase driver awareness of the surroundings. This should result in improved safety and may optimize traffic. However, VC systems are vulnerable to cyber attacks involving message manipulation. Research aimed at tackling this problem has resulted in the proposal of multiple authentication protocols. Several existing survey papers have attempted to classify some of these protocols based on a limited set of characteristics. However, to date there is no generic framework to support the comparison of these protocols and provide guidance for design and evaluation. Most existing classifications either use computation complexity of cryptographic techniques as a criterion, or they fail to make connections between different important aspects of authentication. This paper provides such a framework, proposing a new taxonomy to enable a consistent means of classifying authentication schemes based upon seven main criteria. The main contribution of this study is a framework to enable protocol designers and investigators to adequately compare and select authentication schemes when deciding on particular protocols to implement in an application. Our framework can be applied in design, making choices appropriate for the intended context in both intra-vehicle and inter-vehicle communications. We demonstrate the application of our framework using two different types of case study: individual analysis and hypothetical design. Additionally, this work makes several related contributions. We present the network model, outline the applications, list the communication patterns and the underlying standards, and discuss the necessity of using cryptography and key management in VC systems. We also review the threats, authentication, and privacy requirements in vehicular networks.

Standards such as the American IEEE 1609, European ETSI ITS-G5, and Japanese ARIB STD-T109 aim to establish Cooperative Intelligent Transportation Systems (C-ITS) by enabling Vehicular Ad-Hoc Networks (VANETs). In VANETs, vehicles communicate with other vehicles and roadside infrastructure to support latency-critical applications which increase driver awareness of the surroundings. This should result in improved safety and possibly optimizing traffic. However, to secure VANET communications against message manipulation or replaying, security standards such as IEEE 1609.2 and ETSI TS 103 097 are proposed. In this work, we implement the cryptographic primitives recommended in the IEEE 1609.2 standard to authenticate low latency safety critical messages. We evaluate the effect of the implementation using metrics such as CPU clock cycles per operation, average computation time in milliseconds, and message size in bits. We perform a simulation presenting a high-density highway scenario for the above mentioned C-ITS standards. For each standard, we evaluate the number of safety messages that can be successfully received within 100 ms latency. We show how and to what extent the authentication overhead of latency-critical messages may impact on driver safety. Under an assumed traffic scenario, we show that a crash is possible, as a result of the evaluated authentication delay. We show that the recommended algorithms with specific parameters can be a potential solution for low latency safety-critical applications in a large scale scenario.

The increasing use of technologies, particularly computing and communication paradigms, has significantly influenced our daily lives. Interconnecting devices and networks provides convenient platforms for information exchange and facilitates pervasive user data collection. This new environment presents serious privacy challenges. User activities can be continuously monitored in both digital and physical realms. Gathered data can be aggregated and analysed, revealing aspects of user behaviour that may not be apparent from a single data point. The very items that facilitate connectivity simultaneously increase the risk of privacy breaches. The data gathered to provide services can also be used for monitoring and surveillance. This paper discerns three novel categories of privacy concerns relating to pervasive user data collection: privacy and user activity in cyberspace, privacy in personal cyber–physical systems, and privacy in proactive user-driven data collection. We emphasise the primary challenges, ranging from identity tracking in browsing histories to intricate issues in opportunistic networks, situating each within practical, real-world scenarios. Furthermore, we assess the effectiveness of current countermeasures, investigating their strengths and limitations. This paper explores the challenges in preserving privacy in user interactions with dynamic interconnected systems and suggests countermeasures to mitigate identified privacy risks.