This dissertation focuses on the forensic validation of computer evidence. It is a burgeoning field, by necessity, and there have been significant advances in the detection and gathering of evidence related to electronic crimes. What makes the computer forensics field similar to other forensic fields is that considerable emphasis is placed on the validity of the digital evidence. It is not just the methods used to collect the evidence that is a concern. What is also a problem is that perpetrators of digital crimes may be engaged in what is called anti-forensics. Digital forensic evidence techniques are deliberately thwarted and corrupted by those under investigation. In traditional forensics the link between evidence and perpetrator's actions is often straightforward: a fingerprint on an object indicates that someone has touched the object. Anti-forensic activity would be the equivalent of having the ability to change the nature of the fingerprint before, or during the investigation, thus making the forensic evidence collected invalid or less reliable. This thesis reviews the existing security models and digital forensics, paying particular attention to anti-forensic activity that affects the validity of data collected in the form of digital evidence. This thesis will build on the current models in this field and suggest a tentative first step model to manage and detect possibility of anti-forensic activity. The model is concerned with stopping anti-forensic activity, and thus is not a forensic model in the normal sense, it is what will be called a “meta-forensic” model. A meta-forensic approach is an approach intended to stop attempts to invalidate digital forensic evidence. This thesis proposes a formal procedure and guides forensic examiners to look at evidence in a meta-forensic way.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:582883 |
| Date | January 2011 |
| Creators | Shanmugam, Karthikeyan |
| Contributors | Powell, R.; Owens, T. |
| Publisher | Brunel University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://bura.brunel.ac.uk/handle/2438/7651 |
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