Authors
Robert Layton, Charles Perez, Babiga Birregah, Paul Watters, Marc Lemercier,
Title
Indirect information linkage for OSINT through authorship analysis of aliases
In
The International Workshop on Data Mining Applications in Industry & Government (DMApps 2013)
Pages
12 p
Year
2013
Indexed by
Abstract
In this paper we examine the problem of automatically link- ing online accounts for open source intelligence gathering.We speci cally aim to determine if two social media accounts are shared by the same au- thor, without the use of direct linking evidence. We pro le the accounts using authorship analysis and nd the best matching guess. We apply this to a series of Twitter accounts identi ed as malicious by a methodology named SPOT and nd several pairs of accounts that belong to the same author, despite no direct evidence linking the two. Overall, our results show that linking aliases is possible with an accuracy of 84%, and using our automated threshold method improves our accuracy to over 90% by removing incorrectly discovered matches.
Affiliations
Offprint