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1
universität innsbruck
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Naively Linking Security to Harm
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Naive Regressions
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How to Model Cyber Risk?
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Measuring Latent Variables via Reflexive Indicators
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Typical Mitigation Study
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Typical Harm Study
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Full Causal Model
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Classifying Studies
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Meta Review of Stock Market Reactions
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Contradictory Data Breach Studies
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Quantifying Cyber Risk is Tricky There is more data about sub-components of complex systems
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Conclusion
Description:
Explore a comprehensive analysis of cyber risk quantification in this 16-minute IEEE presentation. Delve into the challenges of linking security to harm, examine naive regression approaches, and learn how to effectively model cyber risk. Discover techniques for measuring latent variables through reflexive indicators, and analyze typical mitigation and harm studies. Gain insights into full causal models and the classification of various studies in the field. Review meta-analyses of stock market reactions and understand the contradictory nature of data breach studies. Recognize the complexities involved in quantifying cyber risk, especially when dealing with sub-components of complex systems. Conclude with a deeper understanding of the intricacies and importance of cyber risk assessment in today's digital landscape.

SoK- Quantifying Cyber Risk

IEEE
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