Privacy of encrypted voice-over-IP

In this paper, we present an early study on how timing-based traffic analysis attacks can be used to reconstruct the communication on end-to-end VOIP systems by taking advantage of the reduction or suppression of the generation of traffic whenever the sender detects a voice inactivity period. We describe a simple Bayesian classifier to identify simple voice signals from the pattern of packet timings. We then proceed to incorporate context awareness by using a Hidden Markov model. Experiments with very simple symbols show that the effectiveness to reconstruct the voice signal depends significantly on the quality of collected silence suppression information. We conclude by identifying a number of problems that need to be further studied in order to effectively assess the danger of silence suppression based attacks on VOIP systems.