Digital forensics deals with the investigation of cybercrimes. With the growing deployment of cloud computing, mobile computing, and digital banking on the internet, the nature of digital forensics has evolved in recent years, and will continue to do so in the near future. This book presents state-of-the-art techniques to address imminent challenges in digital forensics. In particular, it focuses on cloud forensics, Internet-of-Things (IoT) forensics, and network forensics, elaborating on innovative techniques, including algorithms, implementation details and performance analysis, to demonstrate their practicality and efficacy. The innovations presented in this volume are designed to help various stakeholders with the state-of-the-art digital forensics techniques to understand the real world problems. Lastly, the book will answer the following questions: How do the innovations in digital forensics evolve with the emerging technologies? What are the newest challenges in the field of digital forensics? Contents: Preface About the Editors About the Contributors Digital Forensics for Emerging Technologies: Present and Future (Ehsan Khodayarseresht and Suryadipta Majumdar) Evaluating Deleted File Recovery Tools per NIST Guidelines: Results and Critique (Andrew Meyer and Sankardas Roy) Optimized Feature Selection for Network Anomaly Detection (Aniss Chohra, Paria Shirani, ElMouatez Billah Karbab, and Mourad Debbabi) Forensic Data Analytics for Anomaly Detection in Evolving Networks (Li Yang, Abdallah Moubayed, Abdallah Shami,nAmine Boukhtouta, Parisa Heidari, Stere Preda, Richard Brunner, Daniel Migault, and Adel Larabi) Offloading Network Forensic Analytics to Programmable Data Plane Switches (Kurt Friday, Elias Bou-Harb, Jorge Crichigno, Mark Scanlon, and Nicole Beebe) An Event-Driven Forensic Auditing Framework for Clouds (Habib Louafi, Yue Xin, Masoud Bozorgi, Ronald Ellis, Yosr Jarraya, Makan Pourzandi, and Lingyu Wang) Multi-level Security Investigation for Clouds (Suryadipta Majumdar) Digital Evidence Collection in IoT Environment (Jane Iveatu Obioha, Amaliya Princy Mohan and Habib Louafi) Optimizing IoT Device Fingerprinting Using Machine Learning (Oluwatosin Falola, Habib Louafi, and Malek Mouhoub) Conclusion (Suryadipta Majumdar and Paria Shirani) Readership: Law enforcement agencies involved with digital forensics, industry practitioners in digital forensics, academic and industry researchers in cybersecurity and forensics, undergraduate and graduate students majoring in digital forensics and cybersecurity. Key Features: Provides a big picture of the recent progress in digital forensics while currently exists little effort on a systematic compilation of recent works on digital forensics Provides a good understanding of the development of digital forensics by discussing the traditional forensics approaches for investigation of cybercrime, and highlights the big challenges in adopting those traditional approaches to keep pace with advancement in cloud computing and Internet of Things (IoT) Provides a detailed description of digital forensics techniques with real life examples and thorough implementation