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George Danezis
Researcher at University College London
Publications - 213
Citations - 12903
George Danezis is an academic researcher from University College London. The author has contributed to research in topics: Anonymity & Traffic analysis. The author has an hindex of 59, co-authored 209 publications receiving 11516 citations. Previous affiliations of George Danezis include University of Cambridge & Microsoft.
Papers
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Book ChapterDOI
Covert communications despite traffic data retention
TL;DR: It is shown that Alice and Bob can communicate covertly and anonymously, despite Eve having access to the traffic data of most machines on the Internet.
Proceedings ArticleDOI
ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging
TL;DR: In this paper, a cryptographic construction for privacy-preserving authentication of public keys is proposed, called ClaimChain, which allows users to store claims about their identities and keys, as well as their beliefs about others in ClaimChain.
Posted Content
Coconut: Threshold Issuance Selective Disclosure Credentials with Applications to Distributed Ledgers
TL;DR: Coconut as mentioned in this paper is a selective disclosure credential scheme supporting distributed threshold issuance, public and private attributes, re-randomization, and multiple unlinkable selective attribute revelations, which integrates with blockchains to ensure confidentiality, authenticity and availability even when a subset of credential issuing authorities are malicious or offline.
Journal Article
No right to remain silent: Isolating Malicious Mixes.
TL;DR: Miranda as discussed by the authors uses both the detection of corrupt mixes, as well as detection of faults related to a pair of mixes, without detection of the faulty one among the two, which leads to reduced connectivity for corrupt mixes and reduces their ability to attack.
Journal ArticleDOI
Bayesian Inference of Accurate Population Sizes and FRET Efficiencies from Single Diffusing Biomolecules
TL;DR: A Monte Carlo Markov chain (MCMC) based algorithm is implemented that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps.