Publication

Atom: Horizontally Scaling Strong Anonymity

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Billions of people now have conversations daily over the Internet. A large portion of this communication takes place via secure messaging protocols that offer "end-to-end encryption'" guarantees and resilience to compromise like the widely-used Double Ratc ...

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The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

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The Privacy Power of Correlated Noise in Decentralized Learning

Rachid Guerraoui, Martin Jaggi, Anastasiia Koloskova, Youssef Allouah, Aymane El Firdoussi

Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data. Yet, wi ...

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Private Message Franking with After Opening Privacy

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Recently Grubbs et al. [GLR17] initiated the formal study of message franking protocols. This new type of service launched by Facebook, allows the receiver in a secure messaging application to verifiably report to a third party an abusive message some send ...

2023

Bridging the gap between theoretical and practical privacy technologies for at-risk populations

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With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...

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Anonymous Tokens with Stronger Metadata Bit Hiding from Algebraic MACs

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On the one hand, the web needs to be secured from malicious activities such as bots or DoS attacks; on the other hand, such needs ideally should not justify services tracking people's activities on the web. Anonymous tokens provide a nice tradeoff between ...

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Privacy-Preserving Machine Learning on Graphs

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Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

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Messaging between two parties and in the group setting has enjoyed widespread attention both in practice, and, more recently, from the cryptographic community. One of the main challenges in the area is constructing secure (end-to- end encrypted) and effici ...

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Ludovic Barman, David Lazar

Metadata-private messaging designs that scale to support millions of users are rigid: they limit users to a single device that is online all the time and transmits on short regular intervals, and require users to choose precisely when each of their buddies ...

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As unconventional sources of geoinformation, massive imagery and text messages from open platforms and social media form a temporally quasi-seamless, spatially multiperspective stream, but with unknown and diverse quality. Due to its complementarity to rem ...

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Moby: A Blackout-Resistant Anonymity Network for Mobile Devices

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Internet blackouts are challenging environments for anonymity and censorship resistance. Existing popular anonymity networks (e.g., Freenet, I2P, Tor) rely on Internet connectivity to function, making them impracticable during such blackouts. In such a set ...

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Although encryption hides the content of communications from third parties, metadata, i.e., the information attached to the content (such as the size or timing of communication) can be a rich source of details and context. In this dissertation, we demonstr ...

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Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that synthetic data drawn from generative models preserves the stat ...

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Most communication systems (e.g., e-mails, instant messengers, VPNs) use encryption to prevent third parties from learning sensitive information. However, encrypted communications protect the contents but often leak metadata: the amount of data sent and th ...

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Integrity and Metadata Protection in Data Retrieval

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We offer the first security analysis of cache compression, a promising architectural technique that is likely to appear in future mainstream processors. We find that cache compression has novel security implications because the compressibility of a cache l ...

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Gossip protocols (also called rumor spreading or epidemic protocols) are widely used to disseminate information in massive peer-to-peer networks. These protocols are often claimed to guarantee privacy because of the uncertainty they introduce on the node t ...

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Coding techniques have been well studied and used for improving communication quality by combating noise and mitigating interference. Recently, it has been shown that the same coding techniques can also be exploited to further improve communication perform ...

EPFL2020

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Virtually every connection to an Internet service is preceded by a DNS lookup. Lookups are performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations s ...

INTERNET SOC2020

Symmetric Asynchronous Ratcheted Communication with Associated Data

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Following up mass surveillance and privacy issues, modern secure communication protocols now seek strong security, such as forward secrecy and post-compromise security, in the face of state exposures. To address this problem, ratcheting was thereby introdu ...

Springer, Cham2020