Security professionals are trained skeptics. They poke and prod at other people’s digital creations, expecting them to fail in unexpected ways. Shouldn’t that same skeptical power be turned inward? Shouldn’t practitioners ask: “How do I know that my enterprise security capabilities work? Are they scaling, accelerating, or slowing as the business exposes more value to more people and through more channels at higher velocities?” This is the start of the modern measurement mindset—the mindset that seeks to confront security with data.
The Metrics Manifesto: Confronting Security with Data delivers an examination of security metrics with R, the popular open-source programming language and software development environment for statistical computing. This insightful and up-to-date guide offers readers a practical focus on applied measurement that can prove or disprove the efficacy of information security measures taken by a firm.
The book’s detailed chapters combine topics like security, predictive analytics, and R programming to present an authoritative and innovative approach to security metrics. The author and security professional examines historical and modern methods of measurement with a particular emphasis on Bayesian Data Analysis to shed light on measuring security operations.
Readers will learn how processing data with R can help measure security improvements and changes as well as help technology security teams identify and fix gaps in security. The book also includes downloadable code for people who are new to the R programming language.
Perfect for security engineers, risk engineers, IT security managers, CISOs, and data scientists comfortable with a bit of code, The Metrics Manifesto offers readers an invaluable collection of information to help professionals prove the efficacy of security measures within their company.
Age restriction: 0+
Size: 317 pp.
Total size: 13 MB
Total number of pages: 317
Page size: x мм
Copyright:John Wiley & Sons Limited
The Metrics Manifesto — read a free preview online. Leave comments and reviews, vote for your favorite.