AI & ML
Domain-Invariant and Language-Model-Assisted Acoustic Side-Channel Attacks on Keyboards
arXiv cs.CR0 views
arXiv:2611.13922v1 Announce Type: new Abstract: Acoustic side-channel attacks (ASCA) recover typed text from the sound of keystrokes, using only a commodity microphone and no access to the victim's device. Prior work establishes that such attacks succeed under idealized laboratory conditions - a single keyboard, a fixed microphone, a quiet room, and training and testing on the same device but leaves open the question that matters for security: whether keystroke inference survives the open world of unseen keyboards, diverse users, noisy environments, and compressed transmission channels. The answer developed here is that it does, provided the acoustic model is made explicitly domain-invariant and its noisy predictions are corrected by a language model.
Source：https://arxiv.org/abs/2611.13922PreviousOn Private Knowledge Retrieval and Private Inference for secure multi-agent systemsNextData4Cyber: Labeled Cyber-Physical Datasets for Distribution-Grid Management Systems Under Representative OT Attacks
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