Anatomy of compromising email accounts

Khanna, Seema; Chaudhry, Harish

doi:10.1109/icinfa.2012.6246756

Cited by 6 publications

(2 citation statements)

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“…Compromised accounts initially became the object of research interest in e-mail and web services as seen in [22,12]. In a similar scenario to OSNs, users credentials are stolen using malicious link or phishing techniques [14,22].…”

Section: Related Workmentioning

confidence: 99%

“…In a similar scenario to OSNs, users credentials are stolen using malicious link or phishing techniques [14,22]. Concerning e-mails, researches already conducted work in user levels by using social engineering to emphasize user awareness [12], while another different approach combined network information, machine learning and content analysis in order to detect harmful content [22].…”

Section: Related Workmentioning

confidence: 99%

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Recognition of Compromised Accounts on Twitter

Igawa

Almeida

Zarpelão

et al. 2015

Anais Do Simpósio Brasileiro De Sistemas De Informação (SBSI)

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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.

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