How to Measure Anything in Cybersecurity Risk, 2nd Edition

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· Gildan Media · Vorgelesen von Jim Seybert
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In How to Measure Anything in Cybersecurity Risk, Second Edition, a pioneering information security professional and a leader in quantitative analysis methods deliver yet another eye-opening text applying the quantitative language of risk analysis to cybersecurity. In the book, the authors demonstrate how to quantify uncertainty and shed light on how to measure seemingly intangible goals. It's a practical guide to improving risk assessment with a straightforward and simple framework. Advanced methods and detailed advice for a variety of use cases round out the book, which also includes: - A new "Rapid Risk Audit" for a first quick quantitative risk assessment - New research on the real impact of reputation damage - New Bayesian examples for assessing risk with little data - New material on simple measurement and estimation, pseudo-random number generators, and advice on combining expert opinion Dispelling long-held beliefs and myths about information security, How to Measure Anything in Cybersecurity Risk is an essential roadmap for IT security managers, CFOs, risk and compliance professionals, and even statisticians looking for novel new ways to apply quantitative techniques to cybersecurity.

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Autoren-Profil

Douglas W. Hubbard is the inventor of Applied Information Economics (AIE) and the author of The Failure of Risk Management: Why It's Broken and How to Fix It.

Richard Seiersen is coauthor of How to Measure Anything in Cybersecurity Risk and author of The Metrics Manifesto: Confronting Security with Data. He's currently the chief risk officer at Resilience, where he and his team quantitatively model and measure cyber risk.

As a young boy Jim Seybert would dictate stories, telling his parents to "write this down." Fast-forward to the present, and Jim lends his clear, confident voice to some of the most interesting stories of the day: military histories, political commentary, true crime, heroic memoirs, and great fiction.

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