Data-Driven Cybersecurity: Reducing risk with proven metrics

Synopsis

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 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 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

Copyright:

2025

Book Details

Book Quality:

Publisher Quality

Book Size:

352 Pages

ISBN-13:

9781638357650

Related ISBNs:

9781633436107

Publisher:

Manning

Date of Addition:

08/26/25

Copyrighted By:

Manning Publications Co.

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.