Historically, machine learning for information security has prioritized defense: think intrusion detection systems, malware classification and bonnet traffic identification. Offense can benefit from data just as well. Social networks, especially Twitter with its access to extensive personal data, bot-friendly API, colloquial syntax and prevalence of shortened links, are the perfect venues for spreading machine-generated malicious content. We present a recurrent neural network that learns to...
Topics: Youtube, video, Science & Technology, DEF CON, DEFCON, Hacking, Hacker Conference, Computer...