The Case for a Consistent Cyberscam Classification Framework (CCCF)
UIC-ATC '09 Proceedings of the 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Web-based expert systems: benefits and challenges
Information and Management
The Seven Scam Types: Mapping the Terrain of Cybercrime
CTC '10 Proceedings of the 2010 Second Cybercrime and Trustworthy Computing Workshop
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While social media is a new and exciting technology, it has the potential to be misused by organized crime groups and individuals involved in the illicit drugs trade. In particular, social media provides a means to create new marketing and distribution opportunities to a global marketplace, often exploiting jurisdictional gaps between buyer and seller. The sheer volume of postings presents investigational barriers, but the platform is amenable to the partial automation of open source intelligence. This paper presents a new methodology for automating social media data, and presents two pilot studies into its use for detecting marketing and distribution of illicit drugs targeted at Australians. Key technical challenges are identified, and the policy implications of the ease of access to illicit drugs are discussed.