Modern Vulnerability Management: Predictive Cybersecurity

This book comprehensively covers the principles of Risk-based vulnerability management (RBVM) – one of the most challenging tasks in cybersecurity -- from the foundational mathematical models to building your own decision engine to identify, mitigate, and eventually forecast the vulnerabilities that pose the greatest threat to your organization.You will learn: how to structure data pipelines in security and derive and measure value from them; where to procure open-source data to better your organization’s pipeline and how to structure it; how to build a predictive model using vulnerability data; how to measure the return on investment a model in security can yield; which organizational structures and policies work best, and how to use data science to detect when they are not working in security; and ways to manage organizational change around data science implementation. You’ll also be shown real-world examples of how to mature an RBVM program and will understand how to prioritize remediation efforts based on which vulnerabilities pose the greatest risk to your organization.The book presents a fresh approach, rooted in risk management, and taking advantage of rich data and machine learning, helping you focus more on what matters and ultimately make your organization more secure with a system commensurate to the scale of the threat. This is a timely and much-needed book for security managers and practitioners who need to evaluate their organizations and plan future projects and change.Students of cybersecurity will also find this a valuable introduction on how to use their skills in the enterprise workplace to drive change.