Summary of Large Multimodal Agents For Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction, by Fouad Trad et al.
Large Multimodal Agents for Accurate Phishing Detection with Enhanced Token Optimization and Cost Reduction
by Fouad Trad, Ali Chehab
First submitted to arxiv on: 3 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Cryptography and Security (cs.CR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the use of large multimodal agents, specifically Gemini 1.5 Flash and GPT-4o mini, to analyze URLs and webpage screenshots via APIs, enhancing detection performance over using either type alone. The proposed two-tiered agentic approach initially assesses the URL and then evaluates both the URL and screenshot if inconclusive, maintaining robust detection performance while reducing API costs. The cost analysis shows that the agentic approach can process more websites per $100 compared to the multimodal method, providing a viable solution for organizations aiming to leverage advanced AI for phishing detection while controlling expenses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Phishing attacks are getting smarter and trickier, so it’s essential we have good ways to detect them. This paper looks at using special computer programs called agents that can analyze websites’ URLs and what the website looks like on a screen. The researchers found that using these agents together is better than just using one or the other. They also came up with a new way of using these agents that reduces the costs by not asking as many questions. This could be helpful for organizations that want to use advanced AI to detect phishing attacks without breaking the bank. |
Keywords
» Artificial intelligence » Gemini » Gpt
