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Item does not contain fulltext, Both intentional attacks and accidental technical failures can lead to abnormal behaviour in components of industrial control systems. In our previous work, we developed a framework for constructing Bayesian Network (BN) models to enable operators to distinguish between those two classes, including knowledge elicitation to construct the directed acyclic graph of BN models. In this paper, we add a systematic method for knowledge elicitation to construct the Conditional Probability Tables (CPTs) of BN models, thereby completing a holistic framework to distinguish between attacks and technical failures. In order to elicit reliable probabilities from experts, we need to reduce the workload of experts in probability elicitation by reducing the number of conditional probabilities to elicit and facilitating individual probability entry. We utilise DeMorgan models to reduce the number of conditional probabilities to elicit as they are suitable for modelling opposing influences i.e., combinations of influences that promote and inhibit the child event. To facilitate individual probability entry, we use probability scales with numerical and verbal anchors. We demonstrate the proposed approach using an example from the water management domain.

06 juli 2023, Item does not contain fulltext, Professionals working in both the physical and cybersecurity domain need to assess and evaluate security risks. As information on risks in general and security risks in particular is often imperfect and intractable, these professionals are facing a challenge in judging both likelihood and consequences, but how much do their existing psychological biases play a role in these judgments? In this paper, we present new empirical evidence on the perception of the information position and confidence levels of security professionals, the influence of detailed information and the conjunction fallacy, and the level of noise in security assessments. This paper adds to the literature by examining, for the first time, risk assessments by professionals in realistic, real life, security cases. The results show clear indications for overconfidence, comparative ignorance, influence of the conjunction fallacy, and influence of individual experience on security decision making in the professional security domain. The observed phenomena might have far reaching effects on security risk management in organizations and society.

Contains fulltext : 237091.pdf (Publisher’s version ) (Open Access), In this paper, we provide an overview of how Safe-by-Design is conceived and applied in practice in a large number of engineering disciplines. We discuss the differences, commonalities, and possibilities for mutual learning found in those practices and identify several ways of putting those disciplinary outlooks in perspective. The considered engineering disciplines in the order of historically grown technologies are construction engineering, chemical engineering, aerospace engineering, urban engineering, software engineering, bio-engineering, nano-engineering, and finally cyber space engineering. Each discipline is briefly introduced, the technology at issue is described, the relevant or dominant hazards are examined, the social challenge(s) are observed, and the relevant developments in the field are described. Within each discipline the risk management strategies, the design principles promoting safety or safety awareness, and associated methods or tools are discussed. Possible dilemmas that the designers in the discipline face are highlighted. Each discipline is concluded by discussing the opportunities and bottlenecks in addressing safety. Commonalities and differences between the engineering disciplines are investigated, specifically on the design strategies for which empirical data have been collected. We argue that Safe-by-Design is best considered as a specific elaboration of Responsible Research and Innovation, with an explicit focus on safety in relation to other important values in engineering such as well-being, sustainability, equity, and affordability. Safe-by-Design provides for an intellectual venue where social science and the humanities (SSH) collaborate on technological developments and innovation by helping to proactively incorporate safety considerations into engineering practices, while navigating between the extremes of technological optimism and disproportionate precaution. As such, Safe-by-Design is also a practical tool for policymakers an

Contains fulltext : 237105.pdf (Publisher’s version ) (Open Access), Water management infrastructures such as floodgates are critical and increasingly operated by Industrial Control Systems (ICS). These systems are becoming more connected to the internet, either directly or through the corporate networks. This makes them vulnerable to cyber-attacks. Abnormal behaviour in floodgates operated by ICS could be caused by both (intentional) attacks and (accidental) technical failures. When operators notice abnormal behaviour, they should be able to distinguish between those two causes to take appropriate measures, because for example replacing a sensor in case of intentional incorrect sensor measurements would be ineffective and would not block corresponding the attack vector. In the previous work, we developed the attack-failure distinguisher framework for constructing Bayesian Network (BN) models to enable operators to distinguish between those two causes, including the knowledge elicitation method to construct the directed acyclic graph and conditional probability tables of BN models. As a full case study of the attack-failure distinguisher framework, this paper presents a BN model constructed to distinguish between attacks and technical failures for the problem of incorrect sensor measurements in floodgates, addressing the problem of floodgate operators. We utilised experts who associate themselves with the safety and/or security community to construct the BN model and validate the qualitative part of constructed BN model. The constructed BN model is usable in water management infrastructures to distinguish between intentional attacks and accidental technical failures in case of incorrect sensor measurements. This could help to decide on appropriate response strategies and avoid further complications in case of incorrect sensor measurements.

Contains fulltext : 240214.pdf (Publisher’s version ) (Open Access), Cyberattacks against healthcare institutions threaten patient care. The risk of being targeted by a damaging attack is increased when medical devices are used which rely on unmaintained legacy software that cannot be replaced and may have publicly known vulnerabilities. This review aims to provide insight into solutions presented in the literature that mitigate risks caused by legacy software on medical devices. We performed a scoping review by categorising and analysing the contributions of a selection of articles, taken from a literature set discovered through bidirectional citation searching. We found 18 solutions, each fitting at least one of the categories of intrusion detection and prevention, communication tunnelling or hardware protections. Approaches taken include proxying Bluetooth communication through smartphones, behaviour-specification based anomaly detection and authenticating signals based on physical characteristics. These solutions are applicable to various use-cases, ranging from securing pacemakers to medical sensor networks. Most of the solutions are based on intrusion detection and on tunnelling insecure wireless communications. These technologies have distinct application areas, and the decision which one is most appropriate will depend on the type of medical device.