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Towards Better Understanding of Cybercrime: The Role of Fine-Tuned LLMs in Translation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00380664" target="_blank" >RIV/68407700:21230/24:00380664 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/EuroSPW61312.2024.00017" target="_blank" >https://doi.org/10.1109/EuroSPW61312.2024.00017</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/EuroSPW61312.2024.00017" target="_blank" >10.1109/EuroSPW61312.2024.00017</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Better Understanding of Cybercrime: The Role of Fine-Tuned LLMs in Translation

  • Original language description

    Understanding cybercrime communications is paramount for cybersecurity defence. This often involves translating communications into English for processing, interpreting, and generating timely intelligence. The problem is that translation is hard. Human translation is slow, expensive, and scarce. Machine translation is inaccurate and biased. We propose using fine-tuned Large Language Models (LLM) to generate translations that can accurately capture the nuances of cybercrime language. We apply our technique to public chats from the NoName057(16) Russian-speaking hacktivist group. Our results show that our fine-tuned LLM model is better, faster, more accurate, and able to capture nuances of the language. Our method shows it is possible to achieve high-fidelity translations and significantly reduce costs by a factor ranging from 430 to 23,000 compared to a human translator.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/VJ02010020" target="_blank" >VJ02010020: AI-Dojo: Multiagent Testbed for Research and Testing of AI-driven Cybersecurity Technologies</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings - 9th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2024

  • ISBN

    979-8-3503-6729-4

  • ISSN

    2768-0649

  • e-ISSN

    2768-0657

  • Number of pages

    9

  • Pages from-to

    91-99

  • Publisher name

    IEEE Computer Society

  • Place of publication

    Cannes

  • Event location

    Vídeň

  • Event date

    Jul 8, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001302657400011