Bhambri / Khan / Anand | AI Driven Cloud Forensics | Buch | 978-1-041-10716-3 | www.sack.de

Buch, Englisch, 344 Seiten, Format (B × H): 178 mm x 254 mm

Bhambri / Khan / Anand

AI Driven Cloud Forensics

Advanced Techniques for Next Generation Digital Investigations
1. Auflage 2026
ISBN: 978-1-041-10716-3
Verlag: Taylor & Francis

Advanced Techniques for Next Generation Digital Investigations

Buch, Englisch, 344 Seiten, Format (B × H): 178 mm x 254 mm

ISBN: 978-1-041-10716-3
Verlag: Taylor & Francis


Cloud computing has revolutionized digital infrastructure, but it has also introduced complex forensic challenges that demand intelligent, scalable, and automated investigative solutions. AI Driven Cloud Forensics: Advanced Techniques for Next Generation Digital Investigations provides a comprehensive exploration of how artificial intelligence, machine learning, big data analytics, and automation are transforming the future of digital forensics in cloud environments. This edited volume examines advanced methodologies for forensic acquisition in virtual machines, containers, and ephemeral environments; intelligent cloud architectures for secure investigations; and AI-powered frameworks for anomaly detection, fraud investigation, phishing detection, and log analysis. It highlights emerging approaches such as AutoML-enabled forensic systems, federated learning for communication-efficient anomaly detection, AI-centric privileged access management, and real-time detection of data fabrication attacks in decentralized systems. Beyond core forensic technologies, the book addresses interdisciplinary applications across smart micro-grids, dark web environments, digital supply chains, tourism systems, and e-discovery processes. By integrating automation with forensic intelligence, the contributors demonstrate how next-generation digital investigations can become more proactive, predictive, and adaptive. Special emphasis is placed on addressing challenges such as data volatility, multi-tenancy, encryption, jurisdictional constraints, and large-scale log analysis in distributed cloud ecosystems. The book also includes a bibliometric and science-mapping analysis to provide insights into evolving research trends in AI-driven cloud forensic automation. Designed for researchers, cybersecurity professionals, forensic analysts, legal practitioners, cloud architects, and postgraduate students, this volume bridges theoretical foundations with real-world implementations. It serves as a forward-looking reference for building resilient, trustworthy, and AI-enabled forensic ecosystems capable of responding to increasingly sophisticated cyber threats. By combining innovation with investigative rigor, AI Driven Cloud Forensics contributes to shaping the next generation of intelligent digital security and forensic readiness in cloud-driven environments.

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Zielgruppe


Academic, Postgraduate, and Professional Reference

Weitere Infos & Material


Chapter 1 - Introduction to Advanced Cloud Forensics, Chapter 2 - Intelligent Cloud Architecture for Next-Generation Digital Forensics, Chapter 3 - Forensic Acquisition in Ephemeral Environments: Virtual Machines and Containers, Chapter 4 - Forensic Challenges in Emerging Technologies: AI-Driven Cloud Forensics for Next-Generation Digital Investigations, Chapter 5 - Big Data, Machine Learning, and Cloud Forensics: An Integrated Framework for Intelligent Digital Security, Chapter 6 - AI and Automation in Cloud Forensics, Chapter 7 - AI and Automation in Cloud Forensics for Digital Investigations and E-discovery, Chapter 8 - AutoML-Enabled Smart Forensic Framework for Collaborative Crime Analysis and Digital Evidence Prediction, Chapter 9 - Advanced Network Forensics for Cloud Environments, Chapter 10 - Federated Temporal-Attention Network for Communication Efficient Log Anomaly Detection in IoT Environments, Chapter 11 - Two-Tier Real-Time Detection of Data Fabrication Attacks in Decentralized Smart Micro-Grids, Chapter 12 - An Explanatory View of AntiSquat - An AI-Powered Phishing Domain Finder, Chapter 13 - Autonomous Artificial Intelligence Systems for Fraud Detection and Forensics in Dark Web Environment, Chapter 14 - Next-Generation Privileged Access Management: An AI-Centric Perspective, Chapter 15 - Digital Twin and Generative AI Synergies: Pioneering Smart, Predictive, and Autonomous Supply Chain Networks, Chapter 16 - Building Trust and Transparency in Smart Tourism through Cloud-Based Forensic Readiness, Chapter 17 - Mapping Research Trends in AI-Driven Automation for Cloud Forensics: A Bibliometric Analysis and Science Mapping.


Dr. Pankaj Bhambri is an Associate Professor and Convener of the Board of Studies in the Department of Information Technology at Guru Nanak Dev Engineering College, Ludhiana, India. Recognized among the Top 2% of Scientists globally by Stanford University and Elsevier (2025), he has over twenty-one years of teaching and research experience. He earned his Ph.D. in Computer Science and Engineering from I.K.G. Punjab Technical University, Jalandhar. He is currently pursuing a Post Doctorate Fellowship from Lincoln University College, Malaysia.

His research interests span machine learning, bioinformatics, cloud computing, and IoT. Dr. Bhambri has an extensive publication record, with numerous papers in high-impact SCIE and Scopus-indexed journals. He is a prolific author and editor, having contributed to and edited over two dozen books with prestigious publishers like Springer, CRC Press (Taylor & Francis), Elsevier, and IGI Global. He serves as a reviewer and technical committee member for numerous international conferences. Dr. Bhambri has also filed several patents, including an Australian innovation patent. He actively guides multiple Ph.D. scholars in cutting-edge areas of computer science and engineering.

Dr. Mudassir Khan is currently working in the department of Computer Science at College of Science & Arts Tanumah, King Khalid University Abha Saudi Arabia. He has completed his Ph.D. in Computer Science from Noida International University Gautam Budh Nagar (NIU) India. He has completed his Graduation from Aligarh Muslim University, Aligarh and Masters from Gautam Budh Technical University, India. He has more than 12 years of Teaching Experience at the King Khalid University of Saudi Arabia. He has published more than 36 papers in International Journals (SCIE, ESCI, Web of Science, Scopus, Springer and IGI) and conferences (IEEE, Springer Series). He has also published multiple books and patents, too. He is the Member of various technical/ professional societies such as IEEE, UACEE, Internet Society, IAENG and CSTA. His research interest includes Big data, IoT, deep learning, Computer Security, Cyber Security and Cloud Computing.

Dr. A. Jose Anand is currently working as a Professor at, the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, Tamil Nadu. He has one year of industrial experience and twenty-four years of teaching experience. Has one year of experience as assistant staff for Halifax Regional Center for Education at Saint Mary's Elementary School, Halifax, Nova Scotia, Canada. He presented several papers at National Conferences and International Conferences. He published several papers in the National Journal and International Journal and also published books for polytechnic & engineering subjects. He is a Member of CSI, IEI, IET, IETE, ISTE, INS, QCFI and EWB. His current research interest is in Wireless Sensor Networks, Embedded Systems, IoT, Machine Learning and Image Processing, etc.



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