LLMs Have Rhythm: Fingerprinting Large Language Models Using Inter-Token Times and Network Traffic Analysis

<p dir="ltr">As Large Language Models (LLMs) become increasingly integrated into many technological ecosystems across various domains and industries, identifying which model is deployed or being interacted with is critical for the security and trustworthiness of the systems. Current...

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Bibliographic Details
Main Author:	Saeif Alhazbi (17058108) (author)
Other Authors:	Ahmed Hussain (5233775) (author), Gabriele Oligeri (14151426) (author), Panos Papadimitratos (22565177) (author)
Published:	2025
Subjects:	Information and computing sciences Artificial intelligence Cybersecurity and privacy Machine learning Large language models small language models fingerprinting network traffic analysis deep learning network security Computational modeling Analytical models Watermarking Telecommunication traffic Virtual private networks Timing Feature extraction Local area networks
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LLMs Have Rhythm: Fingerprinting Large Language Models Using Inter-Token Times and Network Traffic Analysis

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