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Abstract
In network communications, mixes provide protection against observers hiding the appearance of messages, patterns, length and links between senders and receivers. Statistical disclosure attacks aim to reveal the identity of senders and receivers in a communication network setting when it is protected by standard techniques based on mixes. This work aims to develop a global statistical disclosure attack to detect relationships between users. The only information used by the attacker is the number of messages sent and received by each user for each round, the batch of messages grouped by the anonymity system. A new modeling framework based on contingency tables is used. The assumptions are more flexible than those used in the literature, allowing to apply the method to multiple situations automatically, such as email data or social networks data. A classification scheme based on combinatoric solutions of the space of rounds retrieved is developed. Solutions about relationships between users are provided for all pairs of users simultaneously, since the dependence of the data retrieved needs to be addressed in a global sense.
Highlights
When information is transmitted through the Internet, it is typically encrypted in order to prevent others from being able to view it
Low latency anonymity systems can be used for interactive traffic, for example web applications, instant messaging and others
Mixes are considered the base for building high latency anonymous communication systems
Summary
When information is transmitted through the Internet, it is typically encrypted in order to prevent others from being able to view it. The encryption can be successful, meaning that the keys cannot be guessed within a very long period of time. Even if the data themselves are hidden, other types of information may be vulnerable. In the e-mail framework, anonymity concerns the senders “identity, receivers” identity, the links between senders and receivers, the protocols used, the size of data sent, timings, etc. Since [1] presented the basic ideas of the anonymous communications systems, researchers have developed many mix-based and other anonymity systems for different applications, and attacks on these systems have been developed. Our work aims to develop a global statistical attack to disclose relationships between users in a network based on a single mix anonymity system
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