Pattern-Oriented Memory Forensics
A Pattern Language Approach, Revised Edition
Published on 21. October 2022
Book
Paperback/Softback
98 pages
978-1-912636-76-1 (ISBN)
Description
This short book is a fully revised transcript of a lecture introducing a pattern language for memory forensics - an investigation of past software behavior in memory snapshots. It provides a unified language for discussing and communicating detection and analysis results despite the proliferation of operating systems and tools, a base language for checklists, and aid in accelerated learning. The lecture has a short theoretical part and then illustrates various patterns seen in crash dumps by using WinDbg debugger from Microsoft Debugging Tools for Windows.
More details
Series
Edition
Revised ed.
Language
English
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 280 mm
Width: 216 mm
Thickness: 7 mm
Weight
389 gr
ISBN-13
978-1-912636-76-1 (9781912636761)
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Schweitzer Classification
Persons
Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, inventor, and author. He founded the pattern-oriented software diagnostics, forensics, and prognostics discipline (Systematic Software Diagnostics) and Software Diagnostics and Observability Institute. Vostokov has also authored over 50 books on software diagnostics, anomaly detection and analysis, software and memory forensics, root cause analysis and problem solving, memory dump analysis, debugging, software trace and log analysis, reverse engineering, and malware analysis. He has over 30 years of experience in software architecture, design, development, and maintenance in various industries, including leadership, technical, and people management roles. Dmitry founded OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services). In his spare time, he explores Software Narratology and Quantum Software Diagnostics. His interest areas are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, semiotics, artificial intelligence, machine learning, and data mining to diagnostics and anomaly detection, software diagnostics engineering and diagnostics-driven development, diagnostics workflow and interaction. Recent interest areas also include functional programming, cloud native computing, monitoring, observability, visualization, security, automation, applications of category theory to software diagnostics, development and big data, and diagnostics of artificial intelligence.