Darren Quick - Böcker

To reduce the risk of digital forensic evidence being called into question in judicial proceedings, it is important to have a rigorous methodology and set of procedures for conducting digital forensic investigations and examinations. Digital forensic investigation in the cloud computing environment, however, is in infancy due to the comparatively recent prevalence of cloud computing.

Cloud Storage Forensics presents the first evidence-based cloud forensic framework. Using three popular cloud storage services and one private cloud storage service as case studies, the authors show you how their framework can be used to undertake research into the data remnants on both cloud storage servers and client devices when a user undertakes a variety of methods to store, upload, and access data in the cloud. By determining the data remnants on client devices, you gain a better understanding of the types of terrestrial artifacts that are likely to remain at the Identification stage of an investigation. Once it is determined that a cloud storage service account has potential evidence of relevance to an investigation, you can communicate this to legal liaison points within service providers to enable them to respond and secure evidence in a timely manner.

Learn to use the methodology and tools from the first evidenced-based cloud forensic framework Case studies provide detailed tools for analysis of cloud storage devices using popular cloud storage services Includes coverage of the legal implications of cloud storage forensic investigations Discussion of the future evolution of cloud storage and its impact on digital forensics

This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas.