ANALYSIS OF MULTILAYER-ENCRYPTION ANONYMITY NETWORKS

Abstract

The main goal of multilayer-encryption anonymity networks is to provide a certain level of privacy to their users. At the same time, such networks could be misused to perform harmful network activities. Multilayer-encryption anonymity networks are blocked in some countries. Consequently, different obfuscation techniques are employed by some of these networks to bypass the censorship restriction and enable access to the network by the users. This thesis studies and analyzes multilayer-encryption anonymity networks. Traffic flow analysis is employed to identify multilayer-encryption anonymity networks. The analysis includes collecting data from the three most popular anonymity networks (namely, Tor, JonDonym and I2P). The collected data (Anon17) is made publicly available for researchers on the field. The study also includes proposing weighted factors to quantify and measure the level of anonymity these networks could provide. The flow analysis is used to identify the multilayer-encryption anonymity networks and to identify the obfuscated traffic, if any. Moreover, in this thesis, Packet Momentum is proposed to identify multilayer-encryption anonymity networks. Packet Momentum is a set of appropriate features which could identify multilayer-encryption anonymity networks. The proposed Packet Momentum achieved statistically significant high performance with a low number of packets and a low number of features.