4 citations · 10 across the 20 of their papers we have counts for
6 papers · 1 filter
Large Audio Language Models for Spoofing-Aware Speaker Verification
Sofya Savelyeva, Mariia Perunova, Evgeny Kushnir +3
Recent advances in text-to-speech and voice cloning make high-quality spoofing inexpensive and scalable, threatening voice authentication systems, especially automatic speaker veri…
LLM-Guided Program Evolution for Targeted Black-Box Attacks on Perceptual Hash Algorithms
A. Krylov, D. Rakhov, V. Veselova +2
Perceptual hash algorithms (PHAs) are widely deployed to detect image forgery under benign transformations, yet their robustness against adversarially chosen perturbations remains…
LLM-Guided Prompt Evolution for Password Guessing
Vladimir A. Mazin, Mikhail A. Zorin, Dmitrii S. Korzh +3
Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credential leaks. Automated password…
Probabilistic Verification of Voice Anti-Spoofing Models
Evgeny Kushnir, Alexandr Kozodaev, Dmitrii Korzh +3
Recent advances in generative models have amplified the risk of malicious misuse of speech synthesis technologies, enabling adversaries to impersonate target speakers and access se…
Towards Robust Speech Deepfake Detection via Human-Inspired Reasoning
Artem Dvirniak, Evgeny Kushnir, Dmitrii Tarasov +5
The modern generative audio models can be used by an adversary in an unlawful manner, specifically, to impersonate other people to gain access to private information. To mitigate t…
Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines?
Anton Korznikov, Andrey Galichin, Alexey Dontsov +3
Sparse Autoencoders (SAEs) have emerged as a promising tool for interpreting neural networks by decomposing their activations into sparse sets of human-interpretable features. Rece…