Data-Driven Cybersecurity Reducing risk with proven metrics

Measure, improve, and communicate the value of your security program.
Every business decision should be driven by data-and cyber security is no exception. InData-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 Cybersecuritywill teach you how to:
Align a metrics program with organizational goalsDesign real-time threat detection dashboardsPredictive cybersecurity using AI and machine learningData-driven incident responseApply the ATLAS methodology to reduce alert fatigueCreate compelling metric visualizations
Data-Driven Cybersecurityteaches 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 byJoseph 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 Cybersecurityshows 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 notebooks 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 insideImprove your alert system using the ATLAS frameworkElevate your organization's security postureStatistical and ML techniques for threat detectionExecutive buy-in and strategic investment
About the reader
For readers familiar with the basics of cybersecurity and data analysis.
About the author
Mariano Matteiis 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

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