键盘声学侧信道攻击研究：领域不变性与语言模型辅助

Domain-Invariant and Language-Model-Assisted Acoustic Side-Channel Attacks on Keyboards

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arXiv 论文研究键盘声学侧信道攻击（ASCA），仅用普通麦克风即可从按键声音恢复输入文本，无需接触受害者设备。论文指出，此前攻击只在单一键盘、固定麦克风、安静房间等理想实验室条件下成立，而通过使声学模型具备领域不变性、再用语言模型纠正噪声预测，攻击可在未见过的键盘、多样用户、噪声环境和压缩传输信道等开放场景下依然奏效。

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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.

Subjects:	Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI)
Cite as:	arXiv:2611.13922 [cs.CR]
	(or arXiv:2611.13922v1 [cs.CR] for this version)
	https://doi.org/10.48550/arXiv.2611.13922 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Bikrant Bikram Pratap Maurya [view email]
[v1] Tue, 10 Nov 2026 11:10:42 UTC (75 KB)