Book Review: The Cyber Risk Handbook By Domenic Antonucci

Book Review: The Cyber Risk Handbook Creating and Measuring Effective Cybersecurity Capabilities by Domenic Antonucci. Hoboken, NJ: John Wiley & Sons. pp. 41

Risk perceptions of cyber-security and precautionary behaviour

A quantitative empirical online study examined a set of 16 security hazards on the Internet and two comparisons in 436 UK and US students, measuring perceptions of risk and other risk dimensions. First, perceived risk was highest for identity theft, keylogger, cyber-bullying and social engineering. Second, consistent with existing theory, significant predictors of perceived risk were voluntariness, immediacy, catastrophic potential, dread, severity of consequences and control, as well as Internet experience and frequency of Internet use. Moreover, control was a significant predictor of precautionary behaviour. Methodological implications emphasise the need for non-aggregated analysis and practical implications emphasise risk communication to Internet users

How does intellectual capital align with cyber security?

Purpose – To position the preservation and protection of intellectual capital as a cyber security concern. We outline the security requirements of intellectual capital to help Boards of Directors and executive management teams to understand their responsibilities and accountabilities in this respect.Design/Methodology/Approach – The research methodology is desk research. In other words, we gathered facts and existing research publications that helped us to define key terms, to formulate arguments to convince BoDs of the need to secure their intellectual capital, and to outline actions to be taken by BoDs to do so.Findings – Intellectual capital, as a valuable business resource, is related to information, knowledge and cyber security. Hence, preservation thereof is also related to cyber security governance, and merits attention from boards of directors.Implications – This paper clarifies boards of directors’ intellectual capital governance responsibilities, which encompass information, knowledge and cyber security governance.Social Implications – If boards of directors know how to embrace their intellectual capital governance responsibilities, this will help to ensure that such intellectual capital is preserved and secured.Practical Implications – We hope that boards of directors will benefit from our clarifications, and especially from the positioning of intellectual capital in cyber space.Originality/Value – This paper extends a previous paper published by Von Solms and Von Solms (2018), which clarified the key terms of information and cyber security, and the governance thereof. The originality and value is the focus on the securing of intellectual capital, a topic that has not yet received a great deal of attention from cyber security researchers

Future developments in cyber risk assessment for the internet of things

This article is focused on the economic impact assessment of Internet of Things (IoT) and its associated cyber risks vectors and vertices – a reinterpretation of IoT verticals. We adapt to IoT both the Cyber Value at Risk model, a well-established model for measuring the maximum possible loss over a given time period, and the MicroMort model, a widely used model for predicting uncertainty through units of mortality risk. The resulting new IoT MicroMort for calculating IoT risk is tested and validated with real data from the BullGuard's IoT Scanner (over 310,000 scans) and the Garner report on IoT connected devices. Two calculations are developed, the current state of IoT cyber risk and the future forecasts of IoT cyber risk. Our work therefore advances the efforts of integrating cyber risk impact assessments and offer a better understanding of economic impact assessment for IoT cyber risk

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture

An n-sided polygonal model to calculate the impact of cyber security events

This paper presents a model to represent graphically the impact of cyber events (e.g., attacks, countermeasures) in a polygonal systems of n-sides. The approach considers information about all entities composing an information system (e.g., users, IP addresses, communication protocols, physical and logical resources, etc.). Every axis is composed of entities that contribute to the execution of the security event. Each entity has an associated weighting factor that measures its contribution using a multi-criteria methodology named CARVER. The graphical representation of cyber events is depicted as straight lines (one dimension) or polygons (two or more dimensions). Geometrical operations are used to compute the size (i.e, length, perimeter, surface area) and thus the impact of each event. As a result, it is possible to identify and compare the magnitude of cyber events. A case study with multiple security events is presented as an illustration on how the model is built and computed.Comment: 16 pages, 5 figures, 2 tables, 11th International Conference on Risks and Security of Internet and Systems, (CRiSIS 2016), Roscoff, France, September 201

Risk perceptions of cyber-security and precautionary behaviour

A quantitative empirical online study examined a set of 16 security hazards on the Internet and two comparisons in 436 UK- and US students, measuring perceptions of risk and other risk dimensions. First, perceived risk was highest for identity theft, keylogger, cyber-bullying and social engineering. Second, consistent with existing theory, significant predictors of perceived risk were voluntariness, immediacy, catastrophic potential, dread, severity of consequences and control, as well as Internet experience and frequency of Internet use. Moreover, control was a significant predictor of precautionary behaviour. Methodological implications emphasise the need for non-aggregated analysis and practical implications emphasise risk communication to Internet users