Forensic verification of operating system activity via novel data, acquisition and analysis techniques
Digital Forensics is a nascent field that faces a number of technical, procedural and cultural difficulties that must be overcome if it is to be recognised as a scientific discipline, and not just an art. Technical problems involve the need to develop standardised tools and techniques for the collection and analysis of digital evidence. This thesis is mainly concerned with the technical difficulties faced by the domain. In particular, the exploration of techniques that could form the basis of trusted standards to scientifically verify data. This study presents a set of techniques, and methodologies that can be used to describe the fitness of system calls originating from the Windows NT platform as a form of evidence. It does so in a manner that allows for open investigation into the manner in which the activities described by this form of evidence can be verified.
The performance impact on the Device Under Test (DUT) is explored via the division of the Windows NT system calls into service subsets. Of particular interest to this work is the file subset, as the system calls can be directly linked to user interaction. The subsequent quality of data produced by the collection tool is examined via the use of the Basic Local Alignment Search Tool (BLAST) sequence alignment algorithm. In doing so, this study asserts that system calls provide a recording, or time line, of evidence extracted from the operating system, which represents actions undertaken. In addition, it asserts that these interactions can be compared against known profiles (fingerprints) of activity using BLAST, which can provide a set of statistics relating to the quality of match, and a measure of the similarities of sequences under scrutiny.
These are based on Karlin-Altschul statistics which provides, amongst other values, a P-Value to describe how often a sequence will occur within a search space. The manner in which these statistics are calculated is augmented by the novel generation of the NM1,5_D7326 scoring matrix based on empirical data gathered from the operating system, which is compared against the de facto, biologically generated, BLOSUM62 scoring matrix.
The impact on the Windows 2000 and Windows XP DUTs of monitoring most of the service subsets, including the file subset, is statistically insignificant when simple user interactions are performed on the operating system. For the file subset, p = 0.58 on Windows 2000 Service Pack 4, and p = 0.84 on Windows XP Service Pack 1.
This study shows that if the event occurred in a sequence that originated on an operating system that was not subjected to high process load or system stress, a great deal of confidence can be placed in a gapped match, using either the NM_I.5~7326 or BLOSUM62 scoring matrices, indicating an event occurred, as all fingerprints of interest (FOI) were identified. The worst-case BLOSUM62 P-Value = 1.10E-125, and worst-case NM1.5_D7326 P-Value = 1.60E-72, showing that these matrices are comparable in their sensitivity during normal system conditions.
This cannot be said for sequences gathered during high process load or system stress conditions. The NM1.5_D7326 scoring matrix failed to identify any FOI. The BLOSUM62 scoring matrix returned a number of matches that may have been the FOI, as discerned via the supporting statistics, but were not positively identified within the evaluation criteria.
The techniques presented in this thesis are useful, structured and quantifiable. They provide the basis for a set of methodologies that can be used for providing objective data for additional studies into this form of evidence, which can further explore the details of the calibration and analysis methods, thus supplying the basis for a trusted form of evidence, which may be described as fit-for-purpose.
Graves, J. Forensic verification of operating system activity via novel data, acquisition and analysis techniques. (Thesis). Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/id/eprint/6699
|Deposit Date||Apr 2, 2014|
|Peer Reviewed||Not Peer Reviewed|
|Keywords||novel data; operating systems; forensic computing;|
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