Evidence Reconstruction in Digital Forensics using Fuzzy Methods
to Detect Misused Evidence
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With the rapid development of computer networks the daily work of all trades is more and more dependent on computers. As a result, high-tech crimes, commercial fraud and other phenomena involving computers occur more frequently. So people pay more and more attention to digital forensics. Digital forensics are concerned with the use of digital information (image or document file) as source of evidence in investigations and legal proceedings. This project focuses on the analysis part of digital forensics. Analysis concerned to reconstruct digital evidence and draw conclusions based on the eviden...
With the rapid development of computer networks the daily work of all trades is more and more dependent on computers. As a result, high-tech crimes, commercial fraud and other phenomena involving computers occur more frequently. So people pay more and more attention to digital forensics. Digital forensics are concerned with the use of digital information (image or document file) as source of evidence in investigations and legal proceedings. This project focuses on the analysis part of digital forensics. Analysis concerned to reconstruct digital evidence and draw conclusions based on the evidence found. This project applies fuzzy c-means clustering based on swarm intelligence to digital forensics. The aim of clustering is to partition set of data into clusters. A drawback of clustering is that it easily traps into local minima. To overcome this problem, swarm intelligence is used. Swarm Intelligence is an evolutionary, nature inspired computer technique of global search strategy.
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