UltraSnoop: Placement-agnostic Keystroke Snooping via Smartphone-based Ultrasonic Sonar
-
Published:2023-11-22
Issue:4
Volume:4
Page:1-24
-
ISSN:2691-1914
-
Container-title:ACM Transactions on Internet of Things
-
language:en
-
Short-container-title:ACM Trans. Internet Things
Author:
Zhao Yanchao1ORCID,
Zhao Yiming1ORCID,
Li Si1ORCID,
Han Hao1ORCID,
Xie Lei2ORCID
Affiliation:
1. Nanjing University of Aeronautics and Astronautics, China
2. Nanjing University, China
Abstract
Keystroke snooping is an effective way to steal sensitive information from the victims. Recent research on acoustic emanation-based techniques has greatly improved the accessibility by non-professional adversaries. However, these approaches either require multiple smartphones or require specific placement of the smartphone relative to the keyboards, which tremendously restricts the application scenarios. In this article, we propose UltraSnoop, a training-free, transferable, and placement-agnostic scheme that manages to infer user’s input using a single smartphone placed within the range covered by a microphone and speaker. The innovation of Ultrasnoop is that we propose an ultrasonic anchor-keystroke positioning method and a Mel Frequency Cepstrum Coefficients clustering algorithm, synthesis of which could infer the relative position between the smartphone and the keyboard. Along with the keystroke time difference of arrival, our method could infer the keystrokes and even gradually improve the accuracy as the snooping proceeds. Our real-world experiments show that UltraSnoop could achieve more than 85% top-3 snooping accuracy when the smartphone is placed within the range of 30–60 cm from the keyboard.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
A3 Foresight Program of NSFC
Publisher
Association for Computing Machinery (ACM)
Subject
Software,Information Systems,Hardware and Architecture,Computer Science Applications,Computer Networks and Communications
Reference30 articles.
1. Keyboard acoustic emanations
2. Dictionary attacks using keyboard acoustic emanations
3. EchoTrack: Acoustic device-free hand tracking on smart phones
4. EyeTell: Video-Assisted Touchscreen Keystroke Inference from Eye Movements
5. Yuchi Chen, Gong Wei, Jiangchuan Liu, and Cui Yong. 2017. Fine-grained ultrasound range finding for mobile devices: Sensing way beyond the 24 kHz limit of built-in microphones. In Computer Communications Workshops.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献