GPT-3 and Cybersecurity
Introduction The use of deep neural networks has significantly improved the performance of machine learning in fields such as image […]
Author Younghoo Lee
A Natural Language Query Interface for XDR/SQL
Introduction Many organizations are transitioning their security management to the cloud, where it is much easier to collect and access […]
Black Hat 2022: GPT-3 and Me: How Supercomputer-scale Neural Network Models Apply to Defensive Cybersecurity Problems
BSides LV 2022: GPT-3 and Me: How Supercomputer-Scale Neural Network Models Apply to Defensive Cybersecurity Problems
AI vs AI: Creating Novel Spam and Catching it with Text Generating AI
GPT is a powerful text generation model, but its text generation is unconstrained. This session will discuss how to control GPT to produce sentences which meet specific style or content requirements. The session will review approaches that allow attendees to drive GTP to write SPAM and HAM messages and will demonstrate how to convert GPT into a SPAM filter which detects the generated SPAM.
CatBERT: Context-Aware Tiny BERT for Detecting Targeted Social Engineering Emails
Targeted phishing emails are a major cyber threat on the Internet today and are insufficiently addressed by current defenses. In this paper, we leverage industrial-scale datasets from Sophos cloud email security service, which defends tens of millions of customer mailboxes, to propose a novel Transformer-based architecture for detecting targeted phishing emails. Our model leverages both natural language and email header inputs, is more computationally efficient than competing transformer approaches, and we show that it is less prone to adversarial attacks which deliberately replace keywords with typos or synonyms.
How SophosAI Stops BEC gift card scams
Gift cards are a favorite way for scammers to squeeze money out of their victims. Unlike wire or bank transfers, […]