SecHeadset: A Practical Privacy Protection System for Real-time Voice Communication

Voice communication is convenient while also poses risks of privacy leakage, due to potential interception or eavesdropping during voice transmission. Current protections of voice privacy are almost entirely controlled by communication service providers (CSPs), which operate as a black-box to users thus hard to fully trust. To take back the control of user privacy, in this paper, we introduce SecHeadset, an end-to-end solution for secure voice communication based on voice obfuscation, which is plug-and-play and compatible with various CSPs. Our solution involves two parts. First, we design a voice-like noise masking scheme for voice obfuscation. The noise, mimicking voice characteristics, could effectively obscure users' voices while demonstrating resilience against noise reduction methods. Second, we develop a protocol that enables efficient channel state estimation and secure information exchange between two communication entities. Based on this information, we propose a lightweight algorithm for voice retrieval during communication. We develop a prototype of SecHeadset and evaluate its performance with 8 widely-used applications, including Telegram and Skype. It reduces the voice recognition accuracy of various adversaries to below 15% while maintaining communication quality. We also integrate SecHeadset with off-the-shelf portable devices and verify its real-world effectiveness.

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Published
2025-06-23
DOI
https://doi.org/10.1145/3711875.3729142
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
0.00

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article

SecHeadset: A Practical Privacy Protection System for Real-time Voice Communication

Kun Pan, Zhongjie Ba, Qinglong Wang, Peng Huang et al.
Speech Recognition and Synthesis
article

SecHeadset: A Practical Privacy Protection System for Real-time Voice Communication

Kun Pan, Zhongjie Ba, Qinglong Wang, Peng Huang, Li Lü, Kui Ren, Peng Cheng
article en

Abstract

Voice communication is convenient while also poses risks of privacy leakage, due to potential interception or eavesdropping during voice transmission. Current protections of voice privacy are almost entirely controlled by communication service providers (CSPs), which operate as a black-box to users thus hard to fully trust. To take back the control of user privacy, in this paper, we introduce SecHeadset, an end-to-end solution for secure voice communication based on voice obfuscation, which is plug-and-play and compatible with various CSPs. Our solution involves two parts. First, we design a voice-like noise masking scheme for voice obfuscation. The noise, mimicking voice characteristics, could effectively obscure users' voices while demonstrating resilience against noise reduction methods. Second, we develop a protocol that enables efficient channel state estimation and secure information exchange between two communication entities. Based on this information, we propose a lightweight algorithm for voice retrieval during communication. We develop a prototype of SecHeadset and evaluate its performance with 8 widely-used applications, including Telegram and Skype. It reduces the voice recognition accuracy of various adversaries to below 15% while maintaining communication quality. We also integrate SecHeadset with off-the-shelf portable devices and verify its real-world effectiveness.

Zhejiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 86%
Speech Recognition and Synthesis
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