Privacy-Preserving Photo Sharing based on a Public Key Infrastructure

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Publications associées (31)

Thwarting Malicious Adversaries in Homomorphic Encryption Pipelines

Sylvain Chatel

Homomorphic Encryption (HE) enables computations to be executed directly on encrypted data. As such, it is an auspicious solution for protecting the confidentiality of sensitive data without impeding its usability. However, HE does not provide any guarant ...

EPFL2023

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Bogdan Kulynych

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

EPFL2023

EOS: Efficient Private Delegation of zkSNARK Provers

Yinuo Zhang, Alessandro Chiesa

Succinct zero knowledge proofs (i.e. zkSNARKs) are powerful cryptographic tools that enable a prover to convince a verifier that a given statement is true without revealing any additional information. Their attractive privacy properties have led to much ac ...

Usenix Assoc2023

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Anonymous Tokens with Stronger Metadata Bit Hiding from Algebraic MACs

Serge Vaudenay, Fatma Betül Durak

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 ...

2023

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

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 ...

EPFL2023

Lattice-Based Blind Signatures: Short, Efficient, and Round-Optimal

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We propose a 2-round blind signature protocol based on the random oracle heuristic and the hardness of standard lattice problems (Ring/Module-SIS/LWE and NTRU) with a signature size of 22 KB. The protocol is round-optimal and has a transcript size that can ...

Assoc Computing Machinery2023

Revealing the Structure of Tryptophan in Microhydrated Complexes by Cold Ion Spectroscopy

Oleg Boyarkine, Natalia Nagornova, Manuel Dömer, Andrei Zviagin, Ruslan Yamaletdinov

The geometry of biomolecules isolated in the gas phaseusuallydiffers substantially from their native structures in aqueous solution,which are the only ones truly relevant to life science. To connectthe high resolution of cold ion spectroscopy that can be a ...

2023

New SIDH Countermeasures for a More Efficient Key Exchange

Andrea Basso, Tako Boris Fouotsa

The Supersingular Isogeny Diffie-Hellman (SIDH) protocol has been the main and most efficient isogeny-based encryption protocol, until a series of breakthroughs led to a polynomial-time key-recovery attack. While some countermeasures have been proposed, th ...

Springer2023

Cryptographic Administration for Secure Group Messaging

Serge Vaudenay, Daniel Patrick Collins

Many real-world group messaging systems delegate group administration to the application level, failing to provide formal guarantees related to group membership. Taking a cryptographic approach to group administration can prevent both implementation and pr ...

Berkeley2023

Berry curvature dipole generation and helicity-to-spin conversion at symmetry-mismatched heterointerfaces

Peng Chen, Xupeng Yang

The Berry curvature dipole (BCD) is a key parameter that describes the geometric nature of energy bands in solids. It defines the dipole-like distribution of Berry curvature in the band structure and plays a key role in emergent nonlinear phenomena. The th ...

Nature Portfolio2023

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