VoIPLoc: Passive VoIP call provenance via acoustic side-channels

TL;DR

VoIPLoc is a passive, scalable acoustic fingerprinting method that infers the location of VoIP calls by analyzing echo-related features in audio streams, even over anonymized networks like Tor.

Contribution

It introduces a novel passive location fingerprinting technique exploiting echo features in VoIP audio, enabling remote, undetectable, and robust call provenance inference.

Findings

Effective in fingerprinting locations over Tor network

Robust against noise, codecs, and jitter

Low false-positive rate in experiments

Abstract

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.