Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models

Explore the battle between large language models and smaller human models in phishing detection and creation. How can we stay ahead of scammers using AI-powered emails and human evaluation?

Key takeaways

Phishing is a significant problem, with many email attacks tricking humans.
Researchers are exploring the use of large language models (LLMs) to detect and create phishing emails.
LLMs are getting increasingly good at creating emails that trick people.
The V-triad of credibility, compatibility, and customizability are important factors in creating convincing phishing emails.
Smaller human models can be unstable and may not perform as well as larger LLMs.
Phishing attacks can be made more convincing by targeting specific individuals and using personalized messages.
AI can be used to create realistic emails, but it’s important to not rely solely on AI for detection and instead use a combination of human evaluation and AI-powered tools.
Research is ongoing to improve the detection and creation of phishing emails using LLMs and human models.
It’s important to remain cautious and not rely solely on technology to detect phishing emails.
Using a combination of AI-powered tools and human evaluation can help improve the detection and creation of phishing emails.
LLMs are getting increasingly good at detecting and creating phishing emails, and can be used to enhance spam filters and improve cybersecurity.

Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models

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