Phishing messages typically get 5-10% response rates, but a new system has boosted its rate to 40%. John Seymour and Phil Tully, two data scientists from the security company ZeroFOX, presented their system SNAP_R at Black Hat, a Las Vegas conference on cyber-security, on August 4. SNAP_R uses a deep neural net to study a person's past tweets and then mimics that person's writing style using a Markov model, generating a phishing tweet. So far, there is no reason to think that criminals are using a similar system, but Seymour and Tully's work show how it might be done.

Classified as: phishing, data science in the news, cyber-security, spearphishing, dialogue bots, deep neural networks, Markov model, John Seymour, Black Hat
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Published on: 5 Aug 2016
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