Authors: Veronica Valeros, Anna Širokova, Carlos Catania, Sebastian Garcia

Published on: April 02, 2024

Impact Score: 8.0

Arxiv code: Arxiv:2404.01940

Summary

• What is new: Fine-tuning Large Language Models for translating cybercrime communications, with a focus on accuracy and nuance.
• Why this is important: The difficulty of translating cybercrime communications accurately and efficiently for cyberdefense.
• What the research proposes: Applying fine-tuned Large Language Models to translate communications from Russian-speaking hacktivist groups.
• Results: Achieved high-fidelity translations at significantly reduced costs compared to human translators.

Technical Details

Technological frameworks used: Fine-tuning techniques for Large Language Models

Models used: Large Language Models

Data used: Public chats from the NoName057(16) Russian-speaking hacktivist group

Potential Impact

Cybersecurity firms, translation services, and sectors dependent on timely cyberdefense intelligence.

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