Pwning Social Engineers Using Natural Language Processing Techniques in Email & Non-Email Attacks by Ian Harris + Marcel Carlsson
Advanced Threat Protection by AJ Shipley
Social engineering is a big problem and little progress has been made in stopping it, aside from detection of email phishing. Attacks are launched via vectors in addition to email, e.g. phone, in-person and messaging. Detecting non-email attacks requires a content-based approach that analyzes the meaning of attack messages.
Our first presenters observe that attacks must either ask a question whose answer is private, or command victims to perform a forbidden action. Their approach uses natural language processing techniques to detect questions and commands in messages to determine if they are malicious.
Question answering (QA) approaches, a hot topic in information extraction, attempt to provide answers to factoid questions. Although the current state-of-the-art in QA is imperfect, they have found that even approximate answers are sufficient to determine the privacy of an answer. Their approach was tested on 187,000 emails. They discuss the false positives and false negatives and why this is not an issue in a system deployed for detecting non-email attacks. Demos will be shown.