Title
Recognition of Compromised Accounts on Twitter
Abstract
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.
Year
DOI
Venue
2015
abs/10.5555/2814058.2814061
SBSI 2015 Proceedings of the annual conference on Brazilian Symposium on Information Systems: Information Systems: A Computer Socio-Technical Perspective - Volume 1
Keywords
DocType
Citations 
n grams
Conference
3
PageRank 
References 
Authors
0.38
21
4