Abstract
The emerging, overclocking signal-based acoustic covert communication technique allows smart devices to communicate (without users’ consent) utilizing their microphones and speakers in ultrasonic side channels, which offers users imperceptible and convenient personalized services, e.g., cross-device authentication and media tracking. However, microphones and speakers could be maliciously used and pose severe privacy threats to users. In this paper, we propose a novel high-frequency filtering- (HFF-) based protection model, named UltraFilter, which protects user privacy by enabling users to selectively filter out high-frequency signals from the metadata received by the device. We also analyze the feasibility of using audio frequencies (i.e., ≤18 kHz) to the acoustic covert communication and carry out the acoustic covert communication system by introducing the auditory masking effect. Experiments show that UltraFilter can prevent users’ private information from leaking and reduce system load and that the audio frequencies can pose threats to user privacy.
Highlights
With the rapid development of the Internet of Things (IoT) and smart devices, a user may have more than a smart device [1] for communication and entertainment
Inaudible high-frequency signals that do not affect the user’s perception are filtered and suppressed, so as to protect user privacy (ii) We reveal that acoustic covert communication can be achieved even in the audible spectrum; the acoustic covert communication without user’s perception is finished by employing the auditory masking effect model (iii) We design and implement two prototype systems
We proposed a new security mechanism which uses highfrequency filtering to erase inaudible near-ultrasonic covert signals
Summary
With the rapid development of the Internet of Things (IoT) and smart devices, a user may have more than a smart device [1] for communication and entertainment. Using microphones and speakers in Android devices, acoustic covert communication can provide users with personalized and convenient services, such as cross-device authentication [2] and media tracking-based advertisement. This paper designs and implements a new acoustic highfrequency signal filtering-based security protection mechanism, to address the privacy threats caused by acoustic covert communication attacks to Android devices. Inaudible high-frequency signals (above 18 kHz) that do not affect the user’s perception are filtered and suppressed, so as to protect user privacy (ii) We reveal that acoustic covert communication can be achieved even in the audible spectrum; the acoustic covert communication without user’s perception is finished by employing the auditory masking effect model (iii) We design and implement two prototype systems.
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