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The currently ongoing NIST LWC project aims at identifying new standardization targets for lightweight authenticated encryption with associated data (AEAD) and (optionally) lightweight cryptographic hashing. NIST has deemed it important for performance and ...
Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...
Modern patent systems are slow, inefficient, expensive, and may result in outcomes that actively harm technological progress. This paper proposes a substantive re-think of these systems and lays a foundation upon which practical solutions can be built. Man ...
Distributed ledgers provide high availability and integrity, making them a key enabler for practical and secure computation of distributed workloads among mutually distrustful parties. Many practical applications also require strong confidentiality, howeve ...
Consensus protocols for asynchronous networks are usually complex and inefficient, leading practical systems to rely on synchronous protocols. The invention proposes an approach to simplify asynchronous consensus by building it atop a novel threshold logic ...
2021
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A computer-implemented method and a distributed computer system (100) for privacy- preserving distributed training of a global model on distributed datasets (DS1 to DSn). The system has a plurality of data providers (DP1 to DPn) being communicatively coupl ...
2021
Time travel has always been a fascinating topic in literature and physics. In cryptography, one may wonder how to keep data confidential for some time. In this dissertation, we will study how to make private information travel to the future. This dissertat ...
EPFL2020
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Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...
JMLR-JOURNAL MACHINE LEARNING RESEARCH2021
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Demand Response (DR) is progressively moving from a centralized, unidirectional structure to a set of advanced decentralized mechanisms that better balance distributed supply and demand. This paper presents a decentralized cooperative DR framework to manag ...
As the volume of produced data is exponentially increasing, companies tend to rely on distributed systems to meet the surging demand for storage capacity. With the business workflows becoming more and more complex, such systems often consist of or are acce ...