Social Network Forensics
In the modern world, a new generation of web-based services, such as social network sites have established themselves. By emphasizing openness, community and interaction, these services have had an explosive increase in users over the last years and have become the largest and fastest growing websites on the internet.
Due to the their large user base accompanied by a huge amount of sensitive and personal data, social networking sites can be a rich resource for law enforcement. However, these sites thereby also attract malicious individuals. Therefore the need arises to examine data extraction capabilities from these sites within the scope of an forensic investigation. Whereby, forensic soundness is a claim which can only be made if the underlying forensic process is judged as reliable and appropriate.
In order to do this, first a comprehensive literature review was conducted to further derive a research process model. The research process model is used to answer the underlying research question of this thesis: Is it possible to download all information within a social network (e.g.
Facebook, Twitter, etc.) in a forensically secure manner associated with a targeted individual?
Further, requirements to extract data from Facebook and Twitter are identified. Afterwards the data is extracted by utilizing a data mining technique called Web Scraping in association with the public APIs of both service providers.
This research concludes with the result, that the complete data associated with a targeted individual can only be downloaded with the service provider’s consent. However, despite the identified limitations most of the data was accessible and thereby still give valuable insights in case of an investigation.