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Cyber Threat Intelligence for Cloud Systems

A Comprehensive Guide to Becoming an Analyst

  • 1st Edition - October 1, 2026
  • Latest edition
  • Author: Gianni D'Angelo
  • Language: English

Cyber Threat Intelligence for Cloud Systems: A Comprehensive Guide to Becoming an Analyst begins with the foundational study of asset vulnerabilities, laying the groundwork for un… Read more

Description

Cyber Threat Intelligence for Cloud Systems: A Comprehensive Guide to Becoming an Analyst begins with the foundational study of asset vulnerabilities, laying the groundwork for understanding the weak points within cloud environments. It then introduces tools and methodologies for the automated collection and supervision of data from assets, culminating in the exploration of advanced techniques, such as Artificial Intelligence and Machine Learning for data analysis and automated threat response. Alongside theoretical concepts, the book includes practical examples, hands-on exercises in Python, existing tools, and real-world case studies to help readers solidify their understanding and apply what they’ve learned.

Cybersecurity is one of the fastest-growing fields in today’s technological landscape, and with the increasing complexity and pervasiveness of cyber threats, especially in cloud environments, the need for qualified professionals such as Cyber Threat Analysts has never been more critical. Here, author Gianni D’Angelo provides the technical knowledge required to analyze and defend digital infrastructures, covering both traditional and modern approaches, highlighting how CTI supports decision-making and proactive defense strategies.

Key features

  • Offers a structured learning path that guides readers from the fundamentals of cybersecurity to the specialized knowledge required for working in Cyber Threat Intelligence (CTI) within cloud environments
  • Introduces the foundational principles of CTI, including threat modeling, vulnerability assessment, data collection and correlation, and the lifecycle of threat intelligence
  • Presents a mix of theoretical frameworks, practical exercises, and real-world scenarios, providing readers with the essential skills and mindset to identify, analyze, and respond to cyber threats effectively
  • Covers advanced techniques involving Artificial Intelligence (AI) and Machine Learning (ML) to automate the detection and analysis of cyber threats
  • Demonstrates how to use tools and frameworks to process large volumes of threat data, recognize patterns, and enable rapid, automated responses to security incidents
  • Includes hands-on Python exercises and case studies where readers can learn how to apply AI-driven techniques to real-world cloud environments, thus improving detection accuracy and response speed

Readership

Information security professionals, cybercrime and digital forensic investigators, cyber response and remediation teams, forensic analysts, software developers, e-discovery researchers, security managers, Computer Science analysts, consultants, and researchers in academia and industry. The primary audience also includes Cyber Threat Analysts, AI and ML Engineers in security, cloud engineers, administrators, and DevSecOps professionals applying these techniques to enhance malware detection and predict cyber threats

Table of contents

Part 1: Foundations of Cyber Threat Intelligence and System Vulnerability Analysis: Concepts, Methodologies, and Frameworks for Security Assessment in Cloud and Enterprise Environments

1. Introduction and Motivations

2. Cyber Threat Intelligence

3. What to Protect and From Whom: An Analysis of Threats and Actors

4. Cloud Architecture

5. Vulnerabilities: Fundamentals, Taxonomy, Characterization, and Discovery

6. Cloud Vulnerabilities

Part 2: Practical Cloud Security and Defense.: Hands-On Labs for Offensive and Defensive Techniques

7. Frameworks for Effective Threat Monitoring and Analysis: MITRE ATT&CK & SIEM

8. Automated Threat Detection and Response

9. Virtual Lab for Threat Analysis: Ethics, Network Architecture, and Attack Lifecycle

10. Analyzing and Simulating Attacks on OpenStack Infrastructures

Part 3: Cyber Data Analytics: AI-Powered Threat Analysis

11. Cybersecurity and Big Data

12. Machine Learning and Artificial Intelligence for Cyber Big Data Analysis

13. Practical Data Mining with WEKA

14. Python Libraries for Threat Intelligence

Part 4: Understanding Network Traffic: Analysis, Features, and Classification

15. Intrusion Detection Systems

16. Network Traffic Analysis and Packet Processing

17. Network Traffic Feature Extraction and Analysis

18. Network Traffic Classification

19. Concluding Remarks and Future Directions

Appendix
Bibliography

Product details

  • Edition: 1
  • Latest edition
  • Published: October 1, 2026
  • Language: English

About the author

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Gianni D'Angelo

Dr. Gianni D'Angelo is an Associate Professor at the Department of Computer Science of the University of Salerno, Italy, where he teaches “Cybersecurity and Threat Intelligence for Cloud Systems". He received the M.S. degree (cum laude) in Computer Engineering, and the Ph.D. degree in Computer Science, applied electromagnetism and telecommunications from the University of Salerno.

Affiliations and expertise
University of Salerno, Italy