16 114 193 książek w 175 językach
Jednak się nie przyda? Nic nie szkodzi! U nas możesz zwrócić towar do 30 dni
Bon prezentowy to zawsze dobry pomysł. Obdarowany może za bon prezentowy wybrać cokolwiek z naszej oferty.
30 dni na zwrot towaru
Part 1 Multimedia Evidence Handling includes a discussion on the terminology, real-world requirements, standards, legal aspects and technical challenges regarding multimedia evidence which concern forensics examiners and practitioners in law enforcement and digital forensics/e-discovery industry. It will highlight key differences between computer forensics and multimedia forensics, and the new technical challenges raised from such differences. Part 2 Digital Evidence Extraction bridges digital forensics and multimedia forensics by focusing on extraction of two classes of evidence: 1) non-multimedia evidence that can be extracted from multimedia data via a multimedia processing and analysis process, 2) multimedia evidence that are extracted or enhanced via non-multimedia forensic approaches (e.g. by using traditional computer forensic techniques and tools). Part 3 Multimedia Device and Source Forensics focuses on two main topics: digital forensics of multimedia devices and multimedia source identification. The first topic covers available techniques and tools of analysing multimedia devices to recover different types of evidence, and the second topic is about determining the source of a multimedia artefact (a digital or printed multimedia document). Multimedia devices covered include digital cameras/camcorders, audio recorders and players, scanners, printers. Part 4 Multimedia Content Forensics focuses on forensic analysis and identification of multimedia data which is a core area in the multimedia forensic field. Chapters in this part are about pure digital data, but many techniques are based on physical mechanisms that are involved in the generation of the digital data. Some techniques are also based on multimedia device/source identification from the third part, e.g. image forgery may be detected by exposing clues about mismatch of detected sources of different regions of the same image.