With the increasing deployment of network technologies in industrial control systems (ICSs), cybersecurity has become a challenge in ICSs. Cybersecurity risk assessment (CRA) plays an important role in cybersecurity protection of ICSs. However, the weights of risk indices are constants in traditional CRA methods, and they do not fully consider the requirements of risk identification. In this paper, we define a novel order-α divergence measure for interval-valued intuitionistic fuzzy numbers (IVIFNs) and further develop a novel CRA approach for ICSs based on the proposed divergence measure under an interval-valued intuitionistic fuzzy environment to contribute to the research gap. First, an order-α divergence measure for IVIFNs is defined considering flexibility and robustness of divergence measures with the parameter. Next, a variable weight-based CRA approach for ICSs is developed. In this approach, IVIFNs are adopted to describe evaluation values of risk indices. The weights of risk indices are variable weight vectors and they are determined by the relative divergence closeness. Integration approaches of each node and each attack path in attack-defense trees (ADTs) are proposed based on the operations of IVIFNs, and risk scores of each attack path are calculated by using the score function. Finally, we apply the proposed method to the CRA of a civil aviation fuel supply automatic control system and verify its effectiveness and advantages by comparing it with other methods. This method can dynamically adjust the weights of risk indices considering the relationship between each risk index and the highest risk, and therefore, it can more effectively recognize the highest risk of ICSs than the traditional CRA method. In addition, it can also match the risk attitude of decision-makers by adjusting the parameter α. © 2013 IEEE.

This work presents a roadmap to guide AB’s cybersecurity efforts, adapting existing mechanisms in enterprise information systems, Cyber-Physical Systems, Internet-of-Things, and Industrial Control Systems. We aim to help power and building managers to understand trade-offs to assess risk, model threats, deploy intrusion detection, or simulate the infrastructure. Our contribution also discusses open research questions with respect to cybersecurity, highlighting needed developments for hardening AB and thwarting attacks.

In the contemporary digital landscape, the convergence of artificial intelligence (AI) and big data technologies holds immense promise for revolutionizing cybersecurity practices and fortifying future networks against evolving threats. This paper explores the synergistic potential of AI and big data in creating robust cybersecurity ecosystems capable of effectively mitigating cyber risks and safeguarding critical infrastructures. Through a comprehensive analysis of existing literature and emerging trends, this study elucidates the transformative impact of AI and big data integration in enhancing threat detection, incident response, and risk management strategies. By harnessing the power of AI algorithms for real-time threat analysis and leveraging big data analytics for contextual insights and anomaly detection, organizations can proactively identify and mitigate cyber threats before they escalate into full-blown attacks. The methodology involves a systematic review of relevant literature, followed by a critical analysis of key findings and implications for future research and practice.

The Russia-Ukraine war emphasised how digital technology and the information domain increasingly integrate into modern battlefields. The military strategy began using Robotic and Autonomous Systems (RASs) to enhance tactical and strategic advantages over conventional weaponry and kinetic military action. Evolution in these circumstances increased dependence on cyberspace, algorithms, automation, and robots, creating new opportunities and challenges. Using military RASs in physical warfare can provide relevant operational advantages and open new vulnerabilities, increasing a system attack surface. This research examines military RAS cybersecurity threats, potential vulnerabilities affecting the attack surface, and the importance of responsible and precise technical innovation.

the paper focuses on EU policies in this field and their specificities

This report provides references to analytical reports on cybersecurity from CRS, other government agencies, trade associations, and interest groups.

The primary research question is formulated as follows:
Does the European Union play a significant role in shaping cybersecurity? Correspondingly, the hypothesis adopted to address the research question is as follows: The EU takes actions to enhance resilience against cyberattacks. In the initial section of the article, fundamental concepts of cyber security and cyberspace are defined. Subsequently, EU tools, Union legal regulations, as well as the obligations of key entities pertaining to cyber threats are presented. The main part of the article provides a detailed characterization of new and majorthreats to EU member states

As of 2015, cyber threats have become more prevalent due to high-profile cases like the Target, JPMorgan Chase & Co., Home Depot, and Sony Entertainment breaches. In order to prevent what former Secretary of Defense Leon Panetta characterized as a "Cyber Pearl Harbor," the US government has to engage the private sector in order to build a solid public-private partnership (PPP) for cybersecurity. For there to be a successful cybersecurity PPP between the US government and the private sector, there must be a PPP founded on a model composed of four essential elements: a high level of trust between the public and private entities that corresponds to a mutual belief in the positive gains of both partners; clear baseline guidance imposed from legislation, which should be reinforced with government training and financial incentives; a bottom-up structural approach for efficient operations that allows for more autonomy at lower levels on local needs and resources; and, gaining influential community involvement in the formation of PPPs from all levels of the participating organizations, as well as civil leadership and the general public.

Large-scale development of small-scale generation, and facilities based on this, with their integration into existing distribution networks, qualitatively change the modes and tasks of network management and transform previously passive electric networks into active ones. Features of parameters and modes of small-scale generation, insufficient observability and manageability in centralized management determine the need to use a decentralized multi-agent control of the modes of such networks. First of all, this applies to emergency management, which includes automatic restoration of the integrity and normal operation of the network. This paper presents a set of specialized methods for emergency management of active power grid modes and the results of a study of their effectiveness on mathematical and physical models that confirm the feasibility of using decentralized emergency management and network recovery management. In particular, this includes: a method of emergency proactively balanced separation of grid energy districts along one of the a priori fixed network cross-sections in the event of disturbances with the transition to island mode, and a method for two-stage restoration of the integrity and normal network mode with decentralized synchronization of active parts on remote network switches. In the case of the decentralized remote synchronization of active parts, it is proposed to use special control of the excitation and speed of generators to create conditions for the successful operation of automatic reclosing devices with synchronization detection. It is essential for emergency management in active networks with small generation to reject the concept of ensuring the reliability of power supply through maintaining the integrity of the network in favor of the concept of an emergency-balanced breakdown of the network into balanced areas with the subsequent automatic restoration of integrity. To conduct research on the physical model, a prototype of distributed system emergency automation has been developed that does not use data transmission tools, which ensures its high cybersecurity and the feasibility of decentralized management. © 2023 by the authors.

After 9/11 foresight studies show a shift in security thinking away from a focus on state-centric threats towards a much broader view of security risks recently. This expanded perspective includes risks presented by the vulnerability of European society to the failure of critical infrastructure, to pandemics, environmental change and resource-based conflicts. The chapter places a particular emphasis on the treatment of technological change in these defence and security foresight studies and argues that the growing importance of dual-use technologies is likely to mean that defence will play a declining role as a sponsor and lead user of advanced technologies in the future.