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Understanding social network structure and evolution has important implications for many aspects of network and system design including provisioning, bootstrapping trust and reputation systems via social networks, and defenses against Sybil attacks. Several recent results suggest that augmenting the social network structure with user attributes (e.g.,(More)
We study techniques for identifying an anonymous author via linguistic stylometry, i.e., comparing the writing style against a corpus of texts of known authorship. We experimentally demonstrate the effectiveness of our techniques with as many as 100,000 candidate authors. Given the increasing availability of writing samples online, our result has serious(More)
The effects of social influence and homophily suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. Recently, Yin et al. [28, 29] proposed Social-Attribute Network (SAN), an attribute-augmented social network, to integrate network structure and node attributes to perform(More)
The effects of social influence and homophily suggest that both network structure and node-attribute information should inform the tasks of link prediction and node-attribute inference. Recently, Yin et al. [2010a, 2010b] proposed an attribute-augmented social network model, which we call <i>Social-Attribute Network</i> (SAN), to integrate network structure(More)
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 leveraged the use of social network-based trust relationships to defend against Sybil attacks. However , existing defenses(More)
—In this paper, we conduct the first comprehensive quantification on the perfect de-anonymizability and partial de-anonymizability of real world social networks with seed information in general scenarios, where a social network can follow an arbitrary distribution model. This quantification provides the theoretical foundation for existing structure based(More)
Sybil attacks are a fundamental threat to the security of distributed systems. Recently, there has been a growing interest in leveraging social networks to mitigate Sybil attacks. However, the existing approaches suffer from one or more drawbacks, including bootstrapping from either only known benign or known Sybil nodes, failing to tolerate noise in their(More)
The effects of social influence and network autocorrelation suggest that both network structure and node attribute information should inform the tasks of link prediction and node attribute inference. However , the algorithmic question of how to efficiently incorporate these two sources of information remains largely unanswered. We propose a Social-Attribute(More)
Understanding and modeling the mechanisms by which directed social networks evolve are active areas of research. One related emerging topic is to understand and predict the formation of reciprocal edges, which has many potential applications such as directed social network modeling, friend recommendation, information propagation and targeted spamming.(More)
Mobile devices store a diverse set of private user data and have gradually become a hub to control users' other personal Internet-of-Things devices. Access control on mobile devices is therefore highly important. The widely accepted solution is to protect access by asking for a password. However, password authentication is tedious, e.g., a user needs to(More)