In this paper, we present a rigorous methodology for quantifying the anonymity provided by Tor against a variety of structural attacks, i.e., adversaries that corrupt Tor nodes and thereby perform eavesdropping attacks to deanonymize Tor users. First, we provide an algorithmic approach for computing the anonymity impact of such structural attacks against Tor. The algorithm is parametric in the ...

Data release has privacy disclosure risk if not taking any protection policy. Although attributes that clearly identify individuals, such as Name, Identity Number, are generally removed or decrypted, attackers can still link these databases with other released database on attributes (Quasi-identifiers) to re-identify individual’s private information. K-anonymity is a significant method for priv...

Nowadays, information sharing as an indispensable part appears in our vision, bringing about a mass of discussions about methods and techniques of privacy preserving data publishing which are regarded as strong guarantee to avoid information disclosure and protect individuals’ privacy. Recent work focuses on proposing different anonymity algorithms for varying data publishing scenarios to satis...

Anonymity networks hide user identities with the help of relayed anonymity routers. However, the state-of-the-art anonymitynetworks do not provide an effective trust model. As a result, users cannot circumvent malicious or vulnerable routers, thus makingthem susceptible to malicious router based attacks (e.g., correlation attacks). In this paper, we propose a novel social network based<...

Anonymity technologies enable Internet users to maintain a level of privacy that prevents the collection of identifying information such as the IP address. Understanding the deployment of anonymity technologies on the Internet is important to analyze the current and future trends. In this paper, we provide a tutorial survey and a measurement study to understand the anonymity technology usage on...

Privacy-preserving data mining aims to prevent the exposure of sensitive information as a result of mining algorithms. This is commonly achieved by data anonymisation. One way to anonymise data is by adherence to the k-anonymity concept which requires that the probability to identify an individual by linking databases does not exceed 1/k. In this paper, we propose an algorithm which utilises ro...

In anonymous communication networking, entropy is a popular metric for measuring the average-case difficulty of linking two communicating parties. This paper proposes an alternate view of anonymity, rooted in the observation that global measures of anonymity do not necessarily provide accurate information about the anonymity of an individual user. Such differences can arise due to the character...

Anonymising services have evolved from simple proxies to complex systems. Numerous techniques have been developed to thwart and confuse attackers, thereby improving the degree of anonymity. These techniques are often presented as additional advantages of specific anonymising services. Comparisons of anonymity services exist, however, there is a need for a more structured approach towards the un...

Existing peer-to-peer systems that aim to provide anonymity to its users are based on networks with unstructured or loosely-structured routing algorithms. Structured routing offers performance and robustness guarantees that these systems are unable to achieve. We therefore investigate adding anonymity support to structured peer-to-peer networks. We apply an entropy-based anonymity metric to Cho...

Anonymity means that the identity of the user performing a certain action is maintained secret. The protocols for ensuring anonymity often use random mechanisms which can be described probabilistically. The user, on the other hand, may be selected either nondeterministically or probabilistically. We investigate various notions of anonymity, at different levels of strength, for both the cases of...