Cybersecurity Risk Assessment Research Articles

Minimising cybersecurity risk exposures in industrial control system environments: a techno-human vulnerability analysis approach

ABSTRACT Organisations operating IoT-enabled industrial control systems (ICSs) are concerned about growing cybersecurity risks and impacts to their systems. Cyber-attacks on ICSs demonstrate that technology alone is neither a problem nor a solution to the growing cybersecurity issues affecting these systems. As socio-technical systems, ICSs encompass the functions and interactions of social and technological system elements to enable and/or sustain industrial processes. Thus, a more effective cybersecurity risk management process needs to consider human and technology factors, especially for high-value industrial process targets. Combining critical reviews and gap analysis of existing vulnerability assessment methods with conceptual modelling, a Vulnerability Analysis Critical Impact Point Process (VACIP) methodology is proposed which considers both human and technological vulnerabilities within a cyber-physical system environment to inform an improved insight about attack criticality and impacts. VACIP is validated using a simulated industrial mini testbed; showing that it can enable practicable support for security vulnerability discovery, impact criticality analysis, weak link identification, and prioritised controls. Its novelty is demonstrated in its combination of technology and human vulnerability evaluations in the minimisation of system security exposures. It provides a useful guide for adopting effective cybersecurity risk assessment and exposure reduction strategies.

Ship Cybersecurity Risk Assessment for Safe Operation with Human Involvement: An Experimental Case Study

Ship Cybersecurity Risk Assessment for Safe Operation with Human Involvement: An Experimental Case Study

Integrated physical safety–cyber security risk assessment based on layers of protection analysis

The extensive application of information technology in process industries has increased production efficiency but has also introduced new risks. Therefore, it is necessary to systematically analyse the risks within factories to ensure the stable operation of their production systems. This study proposes an integrated risk assessment method based on layers of protection analysis (LOPA), which combines physical safety and cyber security analyses to provide comprehensive risk assessments for the process industry. The method first identifies the hazardous scenarios and protection layers relevant to a process facility. It then identifies potential cyberattack types and existing countermeasures. Subsequently, the functional impacts of attacks on protection layers and potential coupling relationships are discussed. Using common vulnerability scoring system (CVSS) and semi-quantitative methods, the probability of attack is determined to optimize the probability of failure on demand (PFD) of the protection layers. Finally, a case study of a steam separator in a catalytic cracking unit is used to quantitatively explore the potential attacks and risks of coupled protection layers. The application of Bayesian network (BN) is used for further validation of the method. This study offers a novel quantitative tool for risk assessment in the process industry, which can enhance the security and reliability of industrial production and control systems.

Modeling Cybersecurity Risk: The Integration of Decision Theory and Pivot Pairwise Relative Criteria Importance Assessment with Scale for Cybersecurity Threat Evaluation

This paper presents a comprehensive model for cyber security risk assessment using the PIPRECIA-S method within decision theory, which enables organizations to systematically identify, assess and prioritize key cyber threats. The study focuses on the evaluation of malware, ransomware, phishing and DDoS attacks, using criteria such as severity of impact, financial losses, ease of detection and prevention, impact on reputation and system recovery. This approach facilitates decision making, as it enables the flexible adaptation of the risk assessment to the specific needs of an organization. The PIPRECIA-S model has proven to be useful for identifying the most critical threats, with a special emphasis on ransomware and DDoS attacks, which represent the most significant risks to businesses. This model provides a framework for making informed and strategic decisions to reduce risk and strengthen cyber security, which are critical in a digital environment where threats become more and more sophisticated.

An intuitive approach to cybersecurity risk assessment for non-governmental organizations

Purpose This study proposes a guided tool for cybersecurity risk assessment tailored for nongovernmental organizations (NGOs), enabling them to comply with cybersecurity policies despite limitations in security awareness, funding and expertise. Design/methodology/approach A digital transformation is indispensable for ensuring the sustainable operation of NGOs. Embracing a digital manifesto necessitates an awareness of cybersecurity risks, highlighting the critical need for a robust cybersecurity risk assessment methodology. Initial research phases revealed significant shortages in security awareness, funding and expertise. Consequently, this study introduces an intuitive approach tailored specifically for NGOs, supported by a customized tool designed to address their unique requirements. The NIST cybersecurity risk assessment framework and National Cyber-security Authority (NCA) were adopted to define the risk assessment approach. The efficacy of this approach is evaluated qualitatively through a case study involving three NGOs in Saudi Arabia, aimed at assessing their capability to utilize the tool effectively. Following the implementation, a Likert-scale survey gauged satisfaction among NGOs regarding the tool’s utility. Findings Results from the case study indicate high satisfaction, affirming its alignment with their operational needs and enhancement of compliance with NCA controls. Furthermore, the use of the tool enhances the awareness of NCA’s cybercity requirements and controls. Originality/value Based on theoretical and empirical grounds, this research proposes a novel design of security assessment framework tailored for NGO requirements and supported by initiative tool enabling complying with cybersecurity policies and enhances the awareness of cybersecurity controls.

ProtectingSmall and Medium Enterprises: A Specialized Cybersecurity Risk Assessment Framework and Tool

As the number of Small and Medium Enterprises (SMEs) rises in the world, the amount of sensitive data used also increases, making them targets for cyberattacks. SMEs face a host of issues such as a lack of resources and poor cybersecurity talent, resulting in multiple vulnerabilities that increase overall risk. Cybersecurity risk assessment frameworks have been developed by multiple organizations such as the National Institute of Science and Technology (NIST) and the International Organization for Standardization (ISO), but they are complicated to understand and challenging to implement. This research aimed to create an effective cybersecurity risk assessment framework specifically for SMEs while considering their limitations. This was achieved by first identifying common threats and vulnerabilities and categorizing them according to their importance and risk. Secondly, popular frameworks like the NIST CSF and ISO 27001/2 were analyzed for their proficiencies and deficiencies while identifying relevant areas for SMEs. Finally, novel techniques catered to SMEs were explored and incorporated to create an effective framework for SMEs. This framework was also developed in the form of a tool, providing an interactive and dynamic environment. The tool was effective, and the framework is a promising start but requires more quantitative analysis.

Cyber Security Assessment of An Interoperable Port Call and Voyage Optimization tool

Abstract The MISSION project aims to revolutionize maritime transport by developing a digital tool for real-time optimization of port calls and voyages, thereby reducing fuel consumption, cutting greenhouse gas emissions, and decreasing waiting times through enhanced coordination and information sharing among stakeholders. However, the security of the involved IT systems is critical to ensure safe and reliable operations. This paper introduces harborLang, a novel threat modeling language tailored for the maritime sector, built on the Meta Attack Language (MAL) framework. harborLang addresses the unique security challenges in maritime transport by enabling the modeling and mitigation of potential threats through detailed attack simulations. By integrating harborLang with the Yet Another Cybersecurity Risk Assessment Framework (YACRAF), the project enhances its risk analysis capabilities, allowing for precise threat scenarios that reflect the maritime environment’s complexities. The combined use of harborLang and YACRAF facilitates comprehensive cybersecurity risk assessments, significantly improving decision-making, operational safety, and the overall cybersecurity posture of maritime and port operations.

Penetration Study of Key Technologies for Cybersecurity Risk Assessment

In recent years, with the frequent occurrence of cyber security incidents, people have paid more attention to it. Information security risk assessment is a very important research topic. This paper gives a brief overview of the theory of cybersecurity risk assessment, focuses on the description of the current mainstream cybersecurity risk assessment methods, classifies and compares the existing methods according to the nature of the methods, and analyses the advantages, disadvantages, and application scope of each method. Finally, the main factors affecting the evaluation results are summarized and refined, and future research hotspots in this field are proposed. Through the empirical analysis of the three factors, the influence of the correlation of the three factors, the uncertainty of the evaluation indexes, and the timeliness of the evaluation on the evaluation results are concluded, which provides a reference for future research on evaluation methods.

CYBERSECURITY ON IOT SYSTEMS BASED MULTI-LAYERED SECURITY RISK ASSESSMENT

IoT systems contribute to digital transformation through the development of smart concepts. However, the IoT has also generated new security challenges that require security tools to be adapted, such as risk analysis methodologies. Many organizations use a variety of methods and frameworks to assess cybersecurity risks. However, most current risk assessment methods are for generic software systems, so there is no holistic approach to risk assessment for IoT technologies, especially due to the diversity of IoT systems The purpose of our study is based on the following question: What IoT device factors should be considered in cybersecurity risk assessment methods? In this study we first propose a cybersecurity risk assessment model based on vectors such as vulnerabilities and attacks, which evaluates the security risk from different dimensions of physical layer, network layer and application layer. Secondly, we design the mathematical assessment model for computing risk value of IoT system and then establish the mapping relationship table that the risk value is transformed into risk level.

A simulation framework for automotive cybersecurity risk assessment

Human-initiated disruptions such as cyberattacks on connected vehicles have the potential to cause cascading failures in transport systems, leading to systemic risks. ‘ISO/SAE 21434:2021 Road vehicles - Cybersecurity engineering’ is the current standard for risk management of road vehicles. However, the threat analysis and risk assessment framework given in the standard focuses on asset-level analysis and assessment. Hence, this study develops a novel simulation-based framework to perform threat analysis and risk assessment on connected vehicles from a transport network perspective. The proposed framework is developed based on the ISO/SAE 21434 threat analysis and risk assessment methodology. We demonstrate the applicability and usefulness of the framework through a remote attack via the cellular network on the in-vehicle communication bus system of a connected vehicle to show the potential impacts on the transport network. Based on the findings of our case studies, we exemplify how cyberattacks on individual system components of a connected vehicle have the potential to cause systemic failures.

Cybersecurity risk assessment of a marine dual-fuel engine on inland waterways ship

Cybersecurity risk assessment of a marine dual-fuel engine on inland waterways ship

Charting new waters with CRAMMTS: A survey-driven cybersecurity risk analysis method for maritime stakeholders

This article presents a novel survey-based cybersecurity risk assessment model, CRAMMTS (Cyber Risk Analysis Method for Maritime Transportation Systems), specifically designed for the maritime sector, addressing a critical gap in the literature. Our study contributes significantly in three ways: firstly, through a comprehensive critical literature review of 31 maritime guidelines and 95 scholarly articles, identifying the need for a new cybersecurity risk assessment method; secondly, by developing CRAMMTS, an adaptation of the ISRAM risk analysis method, incorporating the International Maritime Organization's criteria and enabling participation from maritime professionals, especially policymakers and leaders. The third contribution is a case study, the practical application of CRAMMTS in surveying 80 maritime professionals, assessing their perception of cybersecurity risks, and identifying varying risk levels, with the highest associated with cyber threat actors. This approach proved effective in assessing risks at both tactical and strategic levels and providing a clear, quantitative risk metric for decision-making. Our research underscores the maritime sector's need for a holistic, easily implementable cybersecurity risk analysis method that engages leaders and adapts to various Maritime Transportation System scopes, thereby enhancing cybersecurity risk assessment in this crucial domain.

Cyber Resilience Act 2022: A silver bullet for cybersecurity of IoT devices or a shot in the dark?

Internet of Things (IoT) is an ecosystem of interconnected devices (IoT devices) that is capable of intelligent decision making. IoT devices can include everyday objects such as televisions, cars and shoes. The interconnectedness brought forth by IoT has extended the need for cybersecurity beyond the information security realm into the physical security sphere. However, ensuring cybersecurity of IoT devices is far from straightforward because IoT devices have several cybersecurity challenges associated with them. Some of the pertinent cybersecurity challenges of IoT devices in this regard relate to: (i) Security During Manufacturing, (ii) Identification and Authentication, (iii) Lack of Encryption, (iv) Large Attack Surface, (v) Security During Updates, (vi) Lack of User Awareness and (vii) Diverging Standards and Regulations.Against this background, the Cyber Resilience Act (CRA) has been proposed to complement the existing EU cybersecurity framework consisting of legislations such as the Cybersecurity Act and the NIS2 Directive. However, does the CRA provide a framework for effectively combating the cybersecurity challenges of IoT devices in the EU? The central crux of the CRA is to lay down and enforce the rules required to ensure cybersecurity of ‘products with digital elements’, which includes IoT devices. To this end, several obligations are imposed on manufacturers, importers and distributors of IoT devices. Manufacturers are mandated to ensure that the essential cybersecurity requirements prescribed by the CRA are met before placing IoT devices in the market. While the cybersecurity requirements mandated by the CRA are commendable, the CRA suffers from several ambiguities which can hamper its potential impact. For instance, the CRA could provide guidance to manufacturers on how to conduct cybersecurity risk assessment and could clarify the meanings of terms such as “limit attack surfaces” and “without any known exploitable vulnerabilities”.When the fundamental themes of the CRA is analysed from the prism of the cybersecurity challenges of IoT devices, it becomes clear that the CRA does provide a foundation for effectively addressing the cybersecurity challenges of IoT devices. However, the expansive wording in various parts of the CRA, including in the Annex I Requirements, leaves scope for interpretation on several fronts. Consequently, the effectiveness of the CRA in tackling the Security During Manufacturing Challenge, Identification and Authentication Challenge, Large Attack Surface Challenge and Diverging Standards and Regulations Challenge would be largely contingent on how harmonised standards develop and how the industry adopts them. The CRA seems to be more effective, albeit not fully so, in significantly addressing the Lack of Encryption Challenge, Security During Updates Challenge and Lack of User Awareness Challenge of IoT devices. However, the manner in which the CRA addresses all these cybersecurity challenges could be improved upon if an agency such as the ENISA was given the legal mandate to set elaborate standards for cybersecurity requirements under the CRA.

Railway Infrastructure Cybersecurity: An Overview

The railway infrastructure constitutes a type of operational technology (OT)-based critical infrastructure, which is expected to work 24x7, 365 days a year, and where the life expectancy of operational equipment often exceeds 30 years. In this domain, an operational anomaly compromising the OT system can cause a train accident or interrupt traffic, with potentially significant impact in terms of business as well as for passenger safety. Due to their relevance, railways are strategic assets of national interest and, consequently, targets of interest for cybercriminals and cyberwarfare activities. For instance, service interruptions may trigger ripple effects resulting in product shortages and widespread supply chain disruptions, with severe impacts for both the economy and national security. In a bid to optimise and streamline operations. the railway industry has recently started taking a series of significant steps towards digitization, with infrastructures experiencing a significant paradigm shift which, for instance, makes it possible to have centralised interlockings and Radio Block Centre (RBC) for an entire country, with geographical redundancy, ensuring the utmost availability and punctuality by moving the control logic to the cloud. Nevertheless, these developments must always be carried on within the scope of established cybersecurity standards and frameworks. This paper presents an analysis of the state of the art on railway cybersecurity, focused on the existing solutions based on the application of the CENELEC “Technical specification 50701 - Railway Application – Cybersecurity”, which is currently the latest European specification addressing railways, being designed to help suppliers, integrators, and operators to implement a cybersecurity risk assessment plan, the necessary controls, and the management of the complete system life cycle. Special attention will be paid to the conduit between the rail signal interlocking system, that controls the line signalling, and the Automatic Train Supervision (ATS) that runs in the Operational Control Centre (OCC), as this has been identified by the European Union Agency for Cybersecurity (ENISA) as one of the most critical systems identified by the operators of essential services.

Unpacking the Complex Socio-Technical Systems Assemblages in Cybersecurity

The ensuing digital transformation means that cybersecurity solutioning increasingly occurs in the context of complex intractable socio-technical systems comprising non-technical elements, including human, social, and societal factors. These evolving cybersecurity ecosystem dynamics, at the confluence of cyber-physical-social spaces, present several challenges to techno-centric cybersecurity solutions including for risk assessment, threat modelling, and incident analysis. This paper unpacks the complexity of the cybersecurity domain and illustrates the associated socio-technical systems assemblages through a case study and situational analysis of a cybersecurity incident. It then reviews socio-technical systems analysis approaches from the safety management domain and discusses the alignment with and relevance for cybersecurity. The utility of these approaches is demonstrated by applying the functional resonance analysis method to the said cybersecurity incident. The situational analysis surfaces the diverse set of factors, including human, non-human, cultural, economic, institutional, and global, that directly played a role in the unfolding of the incident, and which need to be considered in risk assessment and incident analysis. Further, analysing the incident through the functional resonance analysis method shows the functional dependencies and cascade of performance variability between the different elements in this situation, which goes beyond simple, root-cause, linear causality, and purely technical explanations. Overall, the paper explicates the need for cybersecurity risk assessment and incident analysis that is commensurate with the complexity of underlying socio-technical cyber systems.

Yet Another Cybersecurity Risk Assessment Framework

Yet Another Cybersecurity Risk Assessment Framework

Cyber Security Risk Assessment Methods for Smart Healthcare

The perverseness of the Internet of Things (IoT) has reached the healthcare sector, where interconnected medical devices are transforming how we deliver and manage health. These devices, linked wirelessly, create a vast network known as Internet of Medical Things (IoMT), that integrates seamlessly with the broader healthcare system. This interconnected infrastructure facilitates the exchange of massive amounts of patient data, paving the way for a more distributed and data-driven approach to healthcare. In healthcare’s ICT environment rely heavily on electronic health records (EHR), e-prescribing systems and other systems. Protecting this sensitive data necessitates robust cybersecurity measures. Even though data security is an indirect cost, it is crucial for healthcare systems. In general, patient trust in a healthcare system depends on the infrastructure’s ability to protect data from security and privacy threats. A critical component of this strategy is security risk assessment. A risk is an indirect cost borne by those designing these systems. The risk assessment process identifies, evaluates, and prioritizes potential threats to the organization’s assets including hardware and software. By assessing risks before acting, healthcare organizations can effectively allocate resources to mitigate the most critical vulnerabilities. While broadly applicable cyber risk assessment frameworks like NIST, ISO, and OCTAVE exist, they may lack a strong risk between assets, threats and impacts, and controls. Therefore, they do not provide a comprehensive picture for healthcare specifically. A more thorough examination is required to establish a strong association between protected systems, potential threats, and the resulting risks. This paper critically reviews these frameworks and their methodologies and limitations for healthcare cybersecurity. Even though data security is an indirect cost, it is crucial for healthcare systems.

Harnessing adversarial machine learning for advanced threat detection: AI-driven strategies in cybersecurity risk assessment and fraud prevention

The abstract is "The rapid evolution of cyber threats necessitates innovative defenses, particularly in the domains of risk assessment and fraud detection. This paper explores the integration of Artificial Intelligence (AI) and Adversarial Machine Learning (ML) techniques as a formidable strategy against increasingly sophisticated cyber-attacks. We present a comprehensive framework that leverages AI to dynamically assess cybersecurity risks and detect fraudulent activities with unprecedented accuracy and speed. Firstly, we delve into the foundational principles of adversarial machine learning, outlining how these techniques can be employed to simulate potential cyber threats, thereby enabling the development of more resilient AI-driven cybersecurity systems. We highlight the dual role of adversarial ML in both enhancing security defenses and potentially serving as a vector for sophisticated attacks, underscoring the importance of developing robust, adversarial-resistant models. Subsequently, we introduce a novel adaptive risk assessment methodology that incorporates real-time data analysis, machine learning algorithms, and predictive modeling to accurately identify and prioritize threats. This method adapts to the evolving digital landscape, ensuring that cybersecurity measures are always one step ahead of potential attackers. In the context of fraud detection, we explore -how AI algorithms can sift through vast datasets to detect anomalies and patterns indicative of fraudulent behavior. Through case studies and empirical analysis, we demonstrate the effectiveness of AI in identifying fraud across various sectors, from financial transactions to online identity verification processes. Our research contributes to the cybersecurity field by providing a detailed examination of how AI and adversarial ML can be harnessed to fortify digital defenses, improve risk assessment techniques, and enhance fraud detection capabilities. The insights garnered from this study not only advance theoretical understanding but also offer practical guidance for organizations seeking to implement AI-driven security solutions. As cyber threats continue to evolve, the integration of AI and adversarial ML in cybersecurity strategies will be paramount in safeguarding digital assets and maintaining the integrity of online systems."

Systematic Risk Characterisation of Hardware Threats to Automotive System

The increasing dependence of modern automotive systems on electronics and software poses cybersecurity risks previously not factored into design and engineering of such systems. Attacks on hardware components, communication modules and embedded software – many of which are purposefully designed for automotive control and communications – are the key focus of this paper. We adopt a novel approach to characterise such attacks using Gajski-Kuhn Y-charts to represent attack manipulation across behavioural, structural and physical domains. Our selection of attacks is evidence-driven demonstrating threats that have been demonstrated to be feasible in the real-world. We then risk assess impact of such threats using the recently adopted ISO/SAE 21434 standard for automotive cybersecurity risk assessment, including mitigations for potential adoption. Our work serves to provide unique insights into the complex dynamic of hardware vulnerabilities and how the industry may address system-level security and protection of modern automotive platforms.

BWM Integrated VIKOR method using Neutrosophic fuzzy sets for cybersecurity risk assessment of connected and autonomous vehicles

Connected and autonomous vehicles (CAVs) have gained significant importance in intelligent transportation systems. However, CAVs are associated with significant cyber-risks caused by different threat-agents, which require robust mitigation strategies for secure operation. Different categories of threat-agents come with varying resources, motivation, and skills that must be addressed effectively for the secure operation of CAVs. This study offers a comprehensive analysis of cybersecurity risks from different categories of threat-agents targeting CAVs. A novel hybrid multi-criteria decision making (MCDM) technique has been developed to prioritize the threat-agent categories as part of the cyber defense mechanism. In this study, the major threat-agent categories are identified from the existing literature and cybersecurity reports. Then expert opinion is collected on the likelihood and severity of cyber-attacks undertaken by different threat-agent categories. Single-valued neutrosophic fuzzy sets (SVNFS) are implemented to consolidate the subjectivity of the linguistic opinions given by the experts. Then Best-Worst Method (BWM) is used to determine the relative criteria weightage on the cyber-attack consequences. These weights are then supplied to the ViseKriterijum-ska Optimizacija I Kompromisno Resenj (VIKOR) method for ranking the categories of threat-agents based on the risk perceived by the experts. A case study is presented with five categories of threat-agents and five loss criteria targeting CAVs to validate the viability of the proposed model. The result shows that insider attackers pose maximum risk for cybersecurity of CAVs. The proposed technique will provide helpful insights to the decision-makers for formulating effective defense strategies against cyber-attackers.