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Windows driver memory analysis: A reverse engineering methodology

delete2011-11-01
delete3
PRE
AI
J
James S. Okolica *
G
Gilbert L. Peterson
DOI:10.1016/j.cose.2011.08.001delete
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Abstract

Abstract

En 中文
In a digital forensics examination, the capture and analysis of volatile data provides significant information on the state of the computer at the time of seizure. Memory analysis is a premier method of discovering volatile digital forensic information. While much work has been done in extracting forensic artifacts from Windows kernel structures, less focus has been paid to extracting information from Windows drivers. There are two reasons for this: (1) source code for one version of the Windows kernel (but not associated drivers) is available for educational use and (2) drivers are generally called asynchronously and contain no exported functions. Therefore, finding the handful of driver functions of interest out of the thousands of candidates makes reverse code engineering problematic at best. Developing a methodology to minimize the effort of analyzing these drivers, finding the functions of interest, and extracting the data structures of interest is highly desirable. This paper provides two contributions. First, it describes a general methodology for reverse code engineering of Windows drivers memory structures. Second it applies the methodology to tcpip.sys, a Windows driver that controls network connectivity. The result is the extraction from tcpip.sys of the data structures needed to determine current network connections and listeners from the 32 and 64 bit versions of Windows Vista and Windows 7. Manipulation (DKOM), tcpip.sys, Windows 7, Windows Vista. 2000 MSC: 60, 490. (C) 2011 Elsevier Ltd. All rights reserved.
Keywords:
Digital forensics
Reverse engineering
Direct Kernel Object Manipulation (DKOM)
tcpip.sys
Windows 7
Windows Vista

Journal

C
Computers and Security
IF:
5.4
Papers:
4.6K
Citations:
1.4W

Organization

United States Department of Defense cover
United States Department of Defense
Scholars:
2.8W
Papers: 2.3W
Citations: 172