Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

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.

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Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

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.

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Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

Pattern-Oriented Memory Forensics: A Pattern Language Approach, Revised Edition

Paperback(Revised ed.)

$30.00 
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Overview

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.


Product Details

ISBN-13: 9781912636761
Publisher: Opentask
Publication date: 10/21/2022
Series: Windows Internals Supplements
Edition description: Revised ed.
Pages: 98
Product dimensions: 8.50(w) x 11.00(h) x 0.25(d)

About the Author

Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, and author. He is the founder of pattern-oriented software diagnostics, forensics and prognostics discipline, and Software Diagnostics Institute. Vostokov has also authored more than 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 more than 25 years of experience in software architecture, design, development, and maintenance in a variety of industries including leadership, technical and people management roles. Dmitry also founded Syndromatix, Anolog.io, BriteTrace, DiaThings, Logtellect, OpenTask Iterative and Incremental Publishing, and Software Diagnostics Technology and Services (former Memory Dump Analysis Services) and Software Prognostics. In his spare time, he presents various topics on Debugging TV and explores Software Narratology, its further development as Narratology of Things and Diagnostics of Things (DoT), Software Pathology, and Quantum Software Diagnostics. His current areas of interest are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, 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 cloud native computing, security, automation, functional programming, and applications of category theory to software development and big data.
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