RT Book
T1 Towards Automatic Discovery of Cybercrime Supply Chains
A1 Afroz, Sadia
A2 Shumailov, Ilia
A2 McCoy, Damon
A2 Bhalerao, Rasika
A2 Aliapoulios, Maxwell
LA English
YR 2018
UL https://krimdok.uni-tuebingen.de/Record/1866157248
AB Cybercrime forums enable modern criminal entrepreneurs to collaborate with other criminals into increasingly efficient and sophisticated criminal endeavors. Understanding the connections between different products and services can often illuminate effective interventions. However, generating this understanding of supply chains currently requires time-consuming manual effort. In this paper, we propose a language-agnostic method to automatically extract supply chains from cybercrime forum posts and replies. Our supply chain detection algorithm can identify 36% and 58% relevant chains within major English and Russian forums, respectively, showing improvements over the baselines of 13% and 36%, respectively. Our analysis of the automatically generated supply chains demonstrates underlying connections between products and services within these forums. For example, the extracted supply chain illuminated the connection between hack-for-hire services and the selling of rare and valuable `OG' accounts, which has only recently been reported. The understanding of connections between products and services exposes potentially effective intervention points
K1 slides