What this book covers
Chapter 1, Introduction to the Cloud, presents a fundamental overview of cloud computing, including its architecture, service models (IaaS, PaaS, and SaaS), and deployment types (public, private, and hybrid). Its goal is to refresh or establish basic cloud knowledge, which is essential to comprehend subsequent forensic discussions.
Chapter 2, Trends in Cyber and Privacy Laws and Their Impact on DFIR, provides an in-depth understanding of the legal complexities that arise in cloud-based environments. These complexities include data privacy laws, compliance requirements, and jurisdictional issues. It is crucial to understand the legal framework that governs cloud data and its implications for forensic investigations.
Chapter 3, Exploring the Major Cloud Providers, provides an overview of the major cloud service providers, such as AWS, Azure, and GCP. It explains their unique architectures and services, giving context for how each affects forensic investigations.
Chapter 4, DFIR Investigations – Logs in AWS, provides a detailed guide on conducting DFIR in AWS environments, including accessing, interpreting, and analyzing logs to trace activities and identify security incidents.
Chapter 5, DFIR Investigations – Logs in Azure, focuses on leveraging Azure-specific logging mechanisms for forensic investigations.
Chapter 6, DFIR Investigations – Logs in GCP, is devoted to forensic investigations in GCP, with an emphasis on retrieving and analyzing GCP logs, which are a critical component of investigating incidents in GCP environments.
Chapter 7, Cloud Productivity Suites, discusses the challenges of forensic investigations in cloud-based productivity suites, such as Microsoft 365 and Google Workspace, and explores ways to access and analyze data from these widely used business tools.
Chapter 8, The Digital Forensics and Incident Response Process, provides a comprehensive guide to the DFIR process in cloud environments, including the identification, preservation, analysis, and reporting of digital evidence.
Chapter 9, Common Attack Vectors and TTPs, examines common attack vectors and the tactics, techniques, and procedures (TTPs) used in cloud environments to help anticipate and identify potential security incidents.
Chapter 10, Cloud Evidence Acquisition, discusses the challenges of acquiring digital evidence from cloud environments such as AWS, GCP, and Microsoft Azure, emphasizing the best practices to ensure evidence integrity and legal admissibility.
Chapter 11, Analyzing Compromised Containers, is dedicated to the forensic analysis of compromised containers and Kubernetes platforms in cloud environments. This chapter covers how to identify, collect, and analyze evidence from containers that are increasingly used for cloud-based applications.
Chapter 12, Analyzing Compromised Cloud Productivity Suites, discusses forensic strategies to analyze breaches in cloud-based productivity suites.
Each chapter of Cloud Forensics Demystified builds upon the previous one, creating a comprehensive guide that covers both the theoretical and practical aspects of cloud forensics, tailored to a variety of professional needs and interests.
