Biblio

Internet censorship is used in many parts of the world to prohibit free access to online information. Different techniques such as IP address or URL blocking, DNS hijacking, or deep packet inspection are used to block access to specific content on the Internet. In response, several censorship circumvention systems were proposed that attempt to bypass existing filters. Especially systems that hide the communication in different types of cover protocols attracted a lot of attention. However, recent research results suggest that this kind of covert traffic can be easily detected by censors. In this paper, we present SkypeLine, a censorship circumvention system that leverages Direct-Sequence Spread Spectrum (DSSS) based steganography to hide information in Voice-over-IP (VoIP) communication. SkypeLine introduces two novel modulation techniques that hide data by modulating information bits on the voice carrier signal using pseudo-random, orthogonal noise sequences and repeating the spreading operation several times. Our design goals focus on undetectability in presence of a strong adversary and improved data rates. As a result, the hiding is inconspicuous, does not alter the statistical characteristics of the carrier signal, and is robust against alterations of the transmitted packets. We demonstrate the performance of SkypeLine based on two simulation studies that cover the theoretical performance and robustness. Our measurements demonstrate that the data rates achieved with our techniques substantially exceed existing DSSS approaches. Furthermore, we prove the real-world applicability of the presented system with an exemplary prototype for Skype.

Once data is released to the Internet, there is little hope to successfully delete it, as it may have been duplicated, reposted, and archived in multiple places. This poses a significant threat to users' privacy and their right to permanently erase their very own data. One approach to control the implications on privacy is to assign a lifetime value to the published data and ensure that the data is no longer accessible after this point in time. However, such an approach suffers from the inability to successfully predict the right time when the data should vanish. Consequently, the author of the data can only estimate the correct time, which unfortunately can cause the premature or belated deletion of data. This paper tackles the problem of prefixed lifetimes in data deletion from a different angle and argues that alternative approaches are a desideratum for research. In our approach, we consider different criteria when data should be deleted, such as keeping data available as long as there is sufficient interest for it or untimely delete it in cases of excessive accesses. To assist the self-destruction of data, we propose a protocol and develop a prototype, called Neuralyzer, which leverages the caching mechanisms of the Domain Name System (DNS) to ensure the successful deletion of data. Our experimental results demonstrate that our approach can completely delete published data while at the same time achieving flexible expiration times varying from few days to several months depending on the users' interest.