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Written by DFMag


Digital Profiling

The technological era is rife with new methods and ways to do nearly everything. A vast increase in productivity and improvements are made using computers and all known digital devices. Computer crime and cybercrime is on the rise due to accessibility to the world wide web and the underlying networks from any corner of the Globe. Simple daily tasks and numerous core facilities and infrastructure reside on this global digital data network. Digital Profiling (DP) is a means in which we can analyse and piece together a person’s interaction with this digital data network and produce the outputs of profiling, trend analysis, market statistics, behavioral analysis and apply all this data to the Digital Profile. This information is not only useful to computer crime investigators but anyone who can usefully interpret the data points. Remember each one of us (even those with zero involvement in criminal or suspect activities) all have a digital footprint. Digital profiling is a core part of the broader topic of Criminal Profiling (more information on this is available in earlier issues of DFM). Like all other profiling techniques, DP takes into account the characteristics, behaviours, interactions and other data points that pertain to an individual who interacts with any data source.




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Coming up in the Next issue of Digital Forensics Magazine

Coming up in Issue 37 on sale from November 2018:


Crowd Sourcing Digital Evidence The Risk v The Reward

All digital devices used today can be considered as a potential source for digital evidence. Andrew Ryan investigates the current state in the art of crowd sourced digital evidence. Read More »

Recovery of Forensic Artifacts from Deleted Jump-List in Windows 10

Jump-Lists are widely discussed in forensics community since the release of Windows 7 and are having more capabilities to reveal forensics artifacts in Windows 10. Read More »

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Voice Biometrics

This article looks at the research and development in the field of Voice Biometrics and Speech Analytics, specifically Speaker Identification, Language and Gender Identification, Speech-to-Text Transcription, Keyword Spotting, and others. Read More »

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