Abstract
Massive fraudulent and phishing robocalls present threats to societies. The integration of artificial intelligence technologies, including dialogue and voice generation systems, renders the robocalls more deceptive. Existing countermeasures such as caller ID, call provenance, voiceprint, and fake voice detection have respective limitations and are heavyweight for end users’ smartphones. This paper studies detecting the acoustic echo channel on the remote end of a call based on the received voice. The positive detection result evidencing the physical setup of an audio system is indicative of a human caller. However, the acoustic echo cancellation mechanisms of most audio systems and the use of earphone/headset diminish echoes significantly. To address these issues, the proposed Telesonar transmits short chirps during the vulnerable time of echo cancellation, detects the tiny echo remnants from the received voice, and passively analyzes the timing of caller’s breath sounds to confirm a human caller. Extensive real experiments under a wide range of settings show that Telesonar correctly recognizes human callers with a rate of over 95%, while wrongly recognizing voice robots as human with a rate of 3.8%.
Original language | English |
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Title of host publication | Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys |
Number of pages | 14 |
Publication status | Accepted/In press - 13 Oct 2022 |
Event | The 20th ACM Conference on Embedded Networked Sensor Systems, 2022 - Boston, United States Duration: 6 Nov 2022 → 9 Nov 2022 Conference number: 20 http://sensys.acm.org/2022/ |
Conference
Conference | The 20th ACM Conference on Embedded Networked Sensor Systems, 2022 |
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Abbreviated title | SenSys 2022 |
Country/Territory | United States |
City | Boston |
Period | 6/11/22 → 9/11/22 |
Internet address |
Keywords
- mobile systems
- robocall detection
- internet-of-things systems