Related papers: LinkMirage: How to Anonymize Links in Dynamic Soci…

A growing body of research leverages social network based trust relationships to improve the functionality of the system. However, these systems expose users' trust relationships, which is considered sensitive information in today's…

Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by…

Sybil attacks are becoming increasingly widespread, and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have…

Sybil attacks are becoming increasingly widespread and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have…

Link prediction is one of the fundamental research problems in network analysis. Intuitively, it involves identifying the edges that are most likely to be added to a given network, or the edges that appear to be missing from the network…

In order to prevent the disclosure of privacy-sensitive data, such as names and relations between users, social network graphs have to be anonymised before publication. Naive anonymisation of social network graphs often consists in deleting…

Decentralized identity frameworks grant users full sovereignty over their digital assets in the Web3 ecosystem. However, allowing arbitrary creation of identifiers makes the system susceptible to Sybil attacks and puts assets at risk when…

We investigate the problem of sybil (fake account) detection in social networks from a graph algorithms perspective, where graph structural information is used to classify users as sybil and benign. We introduce the novel notion of user…

Detecting fake users (also called Sybils) in online social networks is a basic security research problem. State-of-the-art approaches rely on a large amount of manually labeled users as a training set. These approaches suffer from three key…

In this paper, we incorporate the realistic scenario of key protection into link privacy preserving and propose the target-link privacy preserving (TPP) model: target links referred to as targets are the most important and sensitive…

Information network analysis has drawn a lot attention in recent years. Among all the aspects of network analysis, similarity measure of nodes has been shown useful in many applications, such as clustering, link prediction and community…

Anonymity networks hide user identities with the help of relayed anonymity routers. However, the state-of-the-art anonymity networks do not provide an effective trust model. As a result, users cannot circumvent malicious or vulnerable…

To date publish of a giant social network jointly from different parties is an easier collaborative approach. Agencies and researchers who collect such social network data often have a compelling interest in allowing others to analyze the…

Privacy issues on social networks have been extensively discussed in recent years. The user identity linkage (UIL) task, aiming at finding corresponding users across different social networks, would be a threat to privacy if unethically…

Social graphs derived from online social interactions contain a wealth of information that is nowadays extensively used by both industry and academia. However, as social graphs contain sensitive information, they need to be properly…

This paper addresses active re-identification attacks in the context of privacy-preserving social graph publication. Active attacks are those where the adversary can leverage fake accounts, a.k.a. sybil nodes, to enforce structural patterns…

The architectures of deployed anonymity systems such as Tor suffer from two key problems that limit user's trust in these systems. First, paths for anonymous communication are built without considering trust relationships between users and…

Social relationships can be divided into different classes based on the regularity with which they occur and the similarity among them. Thus, rare and somewhat similar relationships are random and cause noise in a social network, thus…

Anonymous social networks present a number of new and challenging problems for existing Social Network Analysis techniques. Traditionally, existing methods for analysing graph structure, such as community detection, required global…

The increasing popularity of social media has attracted a huge number of people to participate in numerous activities on a daily basis. This results in tremendous amounts of rich user-generated data. This data provides opportunities for…