2 citations · 3 across the 3 of their papers we have counts for
7 papers
Larger-scale Nakamoto-style Blockchains Don't Necessarily Offer Better Security
Jannik Albrecht, Sebastien Andreina, Frederik Armknecht +3
Extensive research on Nakamoto-style consensus protocols has shown that network delays degrade the security of these protocols. Established results indicate that, perhaps surprisin…
LISA: LIghtweight single-server Secure Aggregation with a public source of randomness
Elina van Kempen, Qifei Li, Giorgia Azzurra Marson +1
Secure Aggregation (SA) is a key component of privacy-friendly federated learning applications, where the server learns the sum of many user-supplied gradients, while individual gr…
Estimating Patch Propagation Times across (Blockchain) Forks
Sebastien Andreina, Lorenzo Alluminio, Giorgia Azzurra Marson +1
The wide success of Bitcoin has led to a huge surge of alternative cryptocurrencies (altcoins). Most altcoins essentially fork Bitcoin's code with minor modifications, such as the…
MITOSIS: Practically Scaling Permissioned Blockchains
Giorgia Azzurra Marson, Sebastien Andreina, Lorenzo Alluminio +2
Scalability remains one of the biggest challenges to the adoption of permissioned blockchain technologies for large-scale deployments. Permissioned blockchains typically exhibit lo…
On the Synchronization Power of Token Smart Contracts
Orestis Alpos, Christian Cachin, Giorgia Azzurra Marson +1
Modern blockchains support a variety of distributed applications beyond cryptocurrencies, including smart contracts -- which let users execute arbitrary code in a distributed and d…
BaFFLe: Backdoor detection via Feedback-based Federated Learning
Sebastien Andreina, Giorgia Azzurra Marson, Helen Möllering +1
Recent studies have shown that federated learning (FL) is vulnerable to poisoning attacks that inject a backdoor into the global model. These attacks are effective even when perfor…