Data Driven Security
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Data-Driven Security
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.
Data-Driven Cybersecurity
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
Intelligent Data-Driven Techniques for Security of Digital Assets
The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality. This book: • Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources. • Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy. • Explains the role of emerging technology such as blockchain technology for transforming conventional business models. • Highlights the importance of machine learning techniques in maintaining the privacy and security of data. • Covers encryption and decryption techniques, their advantages and role in improving the privacy of data. The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.