Data-Driven Cybersecurity
Language: English
Published by Manning Publications Sep 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - Measure, improve, and communicate the value of your security program.Every business decision should be driven by data—and cyber security is no exception. In Data-Driven Cybersecurity, you'll master the art and science of quantifiable cybersecurity, learning to harness data for enhanced threat detection, response, and mitigation. You’ll turn raw data into meaningful intelligence, better evaluate the performance of your security teams, and proactively address the vulnerabilities revealed by the numbers. Data-Driven Cybersecurity will teach you how to: • Align a metrics program with organizational goals • Design real-time threat detection dashboards • Predictive cybersecurity using AI and machine learning • Data-driven incident response • Apply the ATLAS methodology to reduce alert fatigue • Create compelling metric visualizations Data-Driven Cybersecurity teaches you to implement effective, data-driven cybersecurity practices—including utilizing AI and machine learning for detection and prediction. Throughout, the book presents security as a core part of organizational strategy, helping you align cyber security with broader business objectives. If you’re a CISO or security manager, you’ll find the methods for communicating metrics to non-technical stakeholders invaluable. Foreword by Joseph Steinberg. About the technology A data-focused approach to cybersecurity uses metrics, analytics, and automation to detect threats earlier, respond faster, and align security with business goals. About the book Data-Driven Cybersecurity shows you how to turn complex security metrics into evidence-based security practices. You’ll learn to define meaningful KPIs, communicate risk to stakeholders, and turn complex data into clear action. You’ll begin by answering the important questions: what makes a "good" security metric How can I align security with broader business objectives What makes a robust data-driven security management program Python scripts and Jupyter not Elektronisches Buch make collecting security data easy and help build a real-time threat detection dashboards. You’ll even see how AI and machine learning can proactively predict cybersecurity incidents! What's inside • Improve your alert system using the ATLAS framework • Elevate your organization’s security posture • Statistical and ML techniques for threat detection • Executive buy-in and strategic investment About the reader For readers familiar with the basics of cybersecurity and data analysis. About the author Mariano Mattei is a professor at Temple University and an information security professional with over 30 years of experience in cybersecurity and AI innovation. Table of Contents Part 1 Building the foundation 1 Introducing cybersecurity metrics 2 Cybersecurity analytics toolkit 3 Implementing a security metrics program 4 Integrating metrics into business strategy Part 2 The metrics that matter 5 Establishing the foundation 6 Foundations of cyber risk 7 Protecting your assets 8 Continuous threat detection 9 Incident management and recovery Part 3 Beyond the basics: Advanced analytics, machine learning and AI 10 Advanced cybersecurity metrics 11 Advanced statistical analysis 12 Advanced machine learning analysis 13 Generative AI in cybersecurity metrics Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.…
Seller Inventory # 9781633436107
- Title
- Data-Driven Cybersecurity
- Author
- Mattei Matteo
- Publisher
- Manning Publications Sep 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1633436101
- ISBN 13
- 9781633436107
- Item weight
- 654 grams
- Dimensions
- 234x187x22 mm
Drowning in alerts but unsure which ones actually reduce risk? Security teams face an overwhelming flood of data every day, yet it is often unclear which signals matter and how to act on them. Without a structured way to prioritize threats and communicate their impact, even the best analysts struggle to protect their organization. What if you could turn noise into insight and confidently direct resources where they matter most? By aligning metrics with business goals and using real-time data effectively, you can cut through uncertainty and build measurable, trusted security operations.
- ATLAS methodology: Turns scattered alerts into a lifecycle that prioritizes real threats.
- Metric templates: Generate clear KPIs your executives understand, fund, and track.
- Real-time dashboards: See live threat detection and performance on one screen, not ten.
- AI and machine learning: Predict incidents before attackers move, using practical code samples.
- Case studies and exercises: Apply lessons immediately to biotech, pharma, and any regulated industry.
- Visualization techniques: Present results visually so decisions happen fast.
Data-Driven Cybersecurity by veteran CISO Mariano Mattei delivers a complete, format-agnostic field guide to measurable security.
Mattei introduces ATLAS, a step-by-step framework that aligns metrics with business goals and reduces alert fatigue. Hands-on chapters walk you through building dashboards, feeding models, and integrating AI tools, all backed by industry examples. Finish the book able to defend budgets, justify hires, and close gaps with quantifiable proof. Replace gut feelings with dashboards that speak for themselves. Perfect for security analysts, SOC leads, and managers who already know basics and crave actionable, numbers-first guidance.
"Synopsis" may belong to another edition of this title.
About the Author
Mariano Mattei is a VP of Cybersecurity and AI, known for turning data into proactive protection. With three decades in software engineering and C-suite security roles, Mariano brings clear, tool-driven guidance to every page. He distills deep expertise into repeatable frameworks that let readers prove value and cut risk.
"About the title" may belong to another edition of this title.
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