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, DNA, digital evidence and crime scenes.
Computational methods find a place in the forensic sciences in several ways,[1][2][3][4][5] 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 [6], 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.
See also
References
- ^ Computational Forensics Project - Automated Reconstruction of Human Faces (Archival page 6/2002 )
- ^ Wong, J.L. (2004). "Computational forensic techniques for intellectual property protection". IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 23 (6): 987–994. doi:10.1109/TCAD.2004.828122.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help) DIO 10.1109/TCAD.2004.828122 - ^ Propelled Into Computational Forensics by 9/11, NCBI Preps QA Software to ID Katrina Victims (November 28, 2005)
- ^ 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. - ^ Book Announcement: Statistical DNA Forensics: Theory, Methods and Computation (January 2008), Researchandmarkets.com
- ^ YiZhen Huang and YangJing Long (2008). "Demosaicking recognition with applications in digital photo authentication based on a quadratic pixel correlation model" (PDF). Proc. IEEE Conference on Computer Vision and Pattern Recognition: 1–8.
Related Links
- IAPR Technical Committee on Computational Forensics (IAPR-TC6)
- Computational Forensics, Springer Publisher (2008)
- International Journal of Digital Crime and Forensics (IJDCF)
- 3rd International Workshop on Computational Forensics (2009)
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