Projects per year
We propose VoIPLoc, a novel location fingerprinting technique and apply it to the VoIP call provenance problem. It exploits echo-location information embedded within VoIP audio to support fine-grained location inference. We found consistent statistical features induced by the echo-reﬂection characteristics of the location into recorded speech. These features are discernible within traces received at the VoIP destination, enabling location inference. We evaluated VoIPLoc by developing a dataset of audio traces received through VoIP channels over the Tor network. We show that recording locations can be fingerprinted and detected remotely with a low false-positive rate, even when a majority of the audio samples are unlabelled. Finally, we note that the technique is fully passive and thus undetectable, unlike prior art. VoIPLoc is robust to the impact of environmental noise and background sounds, as well as the impact of compressive codecs and network jitter. The technique is also highly scalable and offers several degrees of freedom terms of the fingerprintable space.
|Number of pages
|Accepted/In press - 5 May 2021
|14th ACM Conference on Security and Privacy in Wireless and Mobile Networks 2021 - Virtual Event. Hosted by New York University, Abu Dhabi, United Arab Emirates
Duration: 28 Jun 2021 → 2 Jul 2021
Conference number: 14th
|14th ACM Conference on Security and Privacy in Wireless and Mobile Networks 2021
|ACM WiSec 2021
|United Arab Emirates
|28/06/21 → 2/07/21
- VoIP security
- call provenance
- source identification
- location privacy
- acoustic fingerprint
FingerprintDive into the research topics of 'VoIPLoc: passive VoIP call provenance using acoustic side-channels'. Together they form a unique fingerprint.
- 2 Finished
Revie, C., Ahmed, C. M. & Shah, R.
1/10/18 → 15/02/23
Project: Research Studentship Case - Internally allocated