scholarly journals Cyber risk ordering with rank-based statistical models

2020 ◽  
Author(s):  
Paolo Giudici ◽  
Emanuela Raffinetti
Keyword(s):  
Risk Management ◽  
Statistical Model ◽  
Real World ◽  
Statistical Models ◽  
Risk Models ◽  
Loss Data ◽  
On Line ◽  
Severity Levels ◽  
Cyber Risk

AbstractIn a world that is increasingly connected on-line, cyber risks become critical. Cyber risk management is very difficult, as cyber loss data are typically not disclosed. To mitigate the reputational risks associated with their disclosure, loss data may be collected in terms of ordered severity levels. However, to date, there are no risk models for ordinal cyber data. We fill the gap, proposing a rank-based statistical model aimed at predicting the severity levels of cyber risks. The application of our approach to a real-world case shows that the proposed models are, while statistically sound, simple to implement and interpret.

Obtaining reasonable assurance on cyber resilience

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Filip Caron
Keyword(s):  
Risk Management ◽  
Real World ◽  
Cyber Security ◽  
Design Methodology ◽  
Content Type ◽  
Security Controls ◽  
Conceptual Designs ◽  
Testing Techniques ◽  
Traditional Process ◽  
Cyber Risk

PurposeThe purpose of this paper is to highlight the potential of cyber-testing techniques in assessing the effectiveness of cyber-security controls and obtaining audit evidence.Design/methodology/approachThe paper starts with an identification of the applicable cyber-testing techniques and evaluates their applicability to generally accepted assurance schemes and cyber-security guidelines.FindingsCyber-testing techniques are providing insight in the effectiveness of the actual implementation of cyber-security controls, which may significantly deviate from the conceptual designs of these controls. Furthermore, cyber-testing techniques could provide concise input for cyber-risk management and improvement recommendations.Originality/valueThe presented cyber-testing techniques could complement traditional process-oriented assurance techniques with specialized technical analyses of real-world implementations that focus on the adversaries’ viewpoint.

How Do I Embed Cyber Risk Management in All Aspects of the Organization?

2021 ◽  
pp. 160-172
Author(s):  
Gregory Falco ◽  
Eric Rosenbach
Keyword(s):  
Risk Management ◽  
Real World ◽  
Mitigation Measures ◽  
Critical Systems ◽  
The Real ◽  
Cyber Insurance ◽  
Risk Framework ◽  
Strategic Goals ◽  
Cyber Risk

The question “How do I embed cyber risk management in all aspects of the organization?” addresses how to adopt an Embedded Endurance cyber risk strategy in your day-to-day work as a cyber leader. The chapter begins with a case study about the NotPetya cyberattack, which highlights ongoing challenges in cyber insurance and illuminates the need for embedding cyber mitigation measures across all prioritized critical systems, networks, and data. The chapter describes how to develop an Embedded Endurance cyber risk strategy that is customized for your organization. This chapter walks readers through the key elements of a cyber strategy, from start to finish. This includes defining a risk framework, setting strategic goals, identifying metrics, and establishing strong leadership. The chapter concludes with experiences highlighting the real-world importance of an Embedded Endurance cyber risk strategy from Rosenbach and Falco.

On-line Versus Real World Impressions

2000 ◽  
Author(s):  
Christian End ◽  
Egon Kraan ◽  
Alison Cole ◽  
Jamie Klausner ◽  
Zachary Birchmeier ◽  
...  
Keyword(s):  
Real World ◽  
On Line

Cyber Risk. The New Enemy for Risk Management in the Age of Globalisation

2018 ◽  
pp. 135-155 ◽  
Author(s):  
Chiara Crovini ◽  
Giovanni Ossola ◽  
Pier Luigi Marchini
Keyword(s):  
Risk Management ◽  
Cyber Risk

scholarly journals On the Accuracy of the Sine Power Lomax Model for Data Fitting

Modelling ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 78-104
Author(s):  
Vasili B. V. Nagarjuna ◽  
R. Vishnu Vardhan ◽  
Christophe Chesneau
Keyword(s):  
Statistical Model ◽  
Simulation Study ◽  
Statistical Models ◽  
Goodness Of Fit ◽  
Data Fitting ◽  
Applied Science ◽  
Survival Distribution ◽  
Lomax Distribution ◽  
Model Based

Every day, new data must be analysed as well as possible in all areas of applied science, which requires the development of attractive statistical models, that is to say adapted to the context, easy to use and efficient. In this article, we innovate in this direction by proposing a new statistical model based on the functionalities of the sinusoidal transformation and power Lomax distribution. We thus introduce a new three-parameter survival distribution called sine power Lomax distribution. In a first approach, we present it theoretically and provide some of its significant properties. Then the practicality, utility and flexibility of the sine power Lomax model are demonstrated through a comprehensive simulation study, and the analysis of nine real datasets mainly from medicine and engineering. Based on relevant goodness of fit criteria, it is shown that the sine power Lomax model has a better fit to some of the existing Lomax-like distributions.

Cyber-Risk Management

2000 ◽  
Author(s):  
Ty Sagalow ◽  
Carol Siegel ◽  
Paul Serritella
Keyword(s):  
Risk Management ◽  
Cyber Risk

Cyber-Risk Management

2007 ◽  
pp. 339-354
Author(s):  
Carol Siegel ◽  
Ty Sagalow ◽  
Paul Serritella
Keyword(s):  
Risk Management ◽  
Cyber Risk
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