Authoship Verification, Compromised Accounts, N-grams
In this work, we propose an approach for recognition of compromised Twitter accounts based on Authorship Verification. Our solution can detect accounts that became compromised by analysing their user writing styles. This way, when an account content does not match its user writing style, we affirm that the account has been compromised, similar to Authorship Verification. Our approach follows the profile-based paradigm and uses N-grams as its kernel. Then, a threshold is found to represent the boundary of an account writing style. Experiments were performed using a subsampled dataset from Twitter. Experimental results showed that the developed model is very suitable for compromised recognition of Online Social Networks accounts due to the capability of recognize user styles over 95% accuracy.
Igawa, Rodrigo Augusto; de Almeida, Alex Marino Gonçalves; Zarpelão, Bruno Bogaz; and Barbon, Sylvio Jr, "Recognition of Compromised Accounts on Twitter" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 99.