Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against

Game theory and other group decision-making paradigms, see Gibbons [1992], have been regarded for a long time inadequate in most risk analysis applications. However, thanks to the urge to take into account the strategies of adversaries in contexts such as counter terrorism, economic competition or cybersecurity, a growing interest on these once dismissed methodologies has arisen. Adversarial Risk Analysis (ARA) [Ros Insua et al., 2009] is an emergent frameworkfor supporting a decision-maker (she) who faces opponents (he/they) in conflict situationsfor which the consequences are random and determined by all interacting agents' actions. ARA provides one-sided prescriptive help to the decision-maker, maximising her expected utility while treating her adversaries' decisions as random variables...

This book deals with the state-of-the-art of physical security knowledge and research in the chemical and process industries. Legislation differences between Europe and the USA are investigated, followed by an overview of the how, what and why of contemporary security risk assessment in this particular industrial sector. Innovative solutions such as attractiveness calculations and the use of game theory, advancing the present science of adversarial risk analysis, are discussed. The book further stands up for developing and employing dynamic security risk assessments, for instance based on Bayesian networks, and using OR methods to truly move security forward in the chemical and process industries.

This book pulls together many perspectives on the theory, methods and practice of drawing judgments from panels of experts in assessing risks and making decisions in complex circumstances. The book is divided into four parts: Structured Expert Judgment (SEJ) current research fronts; the contributions of Roger Cooke and the Classical Model he developed; process, procedures and education; and applications. After an Introduction by the Editors, the first part presents chapters on expert elicitation of parameters of multinomial models; the advantages of using performance weighting by advancing the “random expert” hypothesis; expert elicitation for specific graphical models; modelling dependencies between experts’ assessments within a Bayesian framework; preventive maintenance optimization in a Bayesian framework; eliciting life time distributions to parametrize a Dirichlet process; and on an adversarial risk analysis approach for structured expert judgment studies. The second part includes Roger Cooke’s oration from 1995 on taking up his chair at Delft University of Technology; one of the editors reflections on the early decade of the Classical Model development and use; a current overview of the theory of the Classical Model, providing a deep and comprehensive perspective on its foundations and its application; and an interview with Roger Cooke. The third part starts with an interview with Professor Dame Anne Glover, who served as the Chief Scientific Advisor to the President of the European Commission. It then presents chapters on the characteristics of good elicitations by reviewing those advocated and applied; the design and development of a training course for SEJ; and on specific experiences with SEJ protocols with the intention of presenting the challenges and insights collected during these journeys. Finally, the fourth (and largest) part begins with some reflections from Willy Aspinall on his many experiences in applying the Classical Model in several application domains; it continues with related reflections on imperfect elicitations; and then it presents chapters with applications on medicines policy and management, supply chain cyber risk management, geo-political risks, terrorism and the risks facing businesses looking to internationalise.

This study allows readers to get to grips with the conceptual tools and practical techniques for building robust machine learning in the face of adversaries.

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Tackling the cybersecurity challenge is a matter of survival for society at large. Cyber attacks are rapidly increasing in sophistication and magnitude—and in their destructive potential. New threats emerge regularly, the last few years having seen a ransomware boom and distributed denial-of-service attacks leveraging the Internet of Things. For organisations, the use of cybersecurity risk management is essential in order to manage these threats. Yet current frameworks have drawbacks which can lead to the suboptimal allocation of cybersecurity resources. Cyber insurance has been touted as part of the solution – based on the idea that insurers can incentivize companies to improve their cybersecurity by offering premium discounts – but cyber insurance levels remain limited. This is because companies have difficulty determining which cyber insurance products to purchase, and insurance companies struggle to accurately assess cyber risk and thus develop cyber insurance products. To deal with these challenges, this volume presents new models for cybersecurity risk management, partly based on the use of cyber insurance. It contains: A set of mathematical models for cybersecurity risk management, including (i) a model to assist companies in determining their optimal budget allocation between security products and cyber insurance and (ii) a model to assist insurers in designing cyber insurance products. The models use adversarial risk analysis to account for the behavior of threat actors (as well as the behavior of companies and insurers). To inform these models, we draw on psychological and behavioural economics studies of decision-making by individuals regarding cybersecurity and cyber insurance. We also draw on organizational decision-making studies involving cybersecurity and cyber insurance. Its theoretical and methodological findings will appeal to researchers across a wide range of cybersecurity-related disciplines including risk and decision analysis, analytics, technology management, actuarial sciences, behavioural sciences, and economics. The practical findings will help cybersecurity professionals and insurers enhance cybersecurity and cyber insurance, thus benefiting society as a whole. This book grew out of a two-year European Union-funded project under Horizons 2020, called CYBECO (Supporting Cyber Insurance from a Behavioral Choice Perspective).

Are we safer from terrorism today and is our homeland security money well spent? This book offers answers and more.

ASIS Book of The Year Winner as selected by ASIS International, the world's largest community of security practitioners Critical Infrastructure Risk Assessment wins 2021 ASIS Security Book of the Year Award - SecurityInfoWatch ... and Threat Reduction Handbook by Ernie Hayden, PSP (Rothstein Publishing) was selected as its 2021 ASIS Security Industry Book of the Year. As a manager or engineer have you ever been assigned a task to perform a risk assessment of one of your facilities or plant systems? What if you are an insurance inspector or corporate auditor? Do you know how to prepare yourself for the inspection, decided what to look for, and how to write your report? This is a handbook for junior and senior personnel alike on what constitutes critical infrastructure and risk and offers guides to the risk assessor on preparation, performance, and documentation of a risk assessment of a complex facility. This is a definite “must read” for consultants, plant managers, corporate risk managers, junior and senior engineers, and university students before they jump into their first technical assignment.