Computational forensics
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Computational forensics (CF) is a quantitative approach to the methodology of the forensic sciences. It involves computer-based modeling, computer simulation, analysis, and recognition in studying and solving problems posed in various forensic disciplines. CF integrates expertise from computational science and forensic sciences.
A broad range of objects, substances and processes are investigated, which are mainly based on pattern evidence, such as toolmarks, fingerprints, shoeprints, documents etc., but also physiological and behavioral patterns, digital evidence and crime scenes.
Computational methods find a place in the forensic sciences in several ways [1][2], as for example:
- rigorous quantification of individuality,
- definition and establishment of likelihood ratio,
- increase of efficiency and effectiveness in daily forensic casework.
Algorithms implemented are from the fields of signal and image processing, computer vision, computer graphics, data visualization , statistical pattern recognition, data mining, machine learning, and robotics.
Computer forensics (also referred to as digital forensics or forensic information technology) is one specific discipline that could use computational science to study digital evidence. Computational Forensics examines diverse types of evidence.
References
- ^ Computational Forensics Project - Automated Reconstruction of Human Faces (Archival page 6/2002 ) [1]
- ^ Franke, Katrin (2007). "Computational Forensics: Towards Hybrid-Intelligent Crime Investigation". Third International Symposium on Information Assurance and Security, 2007. IAS 2007: 383–386.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help) DOI 10.1109/IAS.2007.84.