2 citations · 3 across the 9 of their papers we have counts for
6 papers · 1 filter
The Power of Backdoor Absorption in Community Training
Issam Seddik, Sami Souihi, Mohamed Tamaazousti +1
Backdoor attacks severely threaten large-scale AI models. When model owners delegate training to external compute providers within a decentralized training paradigm, adversaries ca…
PoTS: Proof-of-Training-Steps for Backdoor Detection in Large Language Models
Issam Seddik, Sami Souihi, Mohamed Tamaazousti +1
As Large Language Models (LLMs) gain traction across critical domains, ensuring secure and trustworthy training processes has become a major concern. Backdoor attacks, where malici…
Adversary-Augmented Simulation for Fairness Evaluation and Defense in Hyperledger Fabric
Erwan Mahe, Rouwaida Abdallah, Pierre-Yves Piriou +1
This paper presents an adversary model and a simulation framework specifically tailored for analyzing attacks on distributed systems composed of multiple distributed protocols, wit…
Order Fairness Evaluation of DAG-based ledgers
Erwan Mahe, Sara Tucci-Piergiovanni
Order fairness in distributed ledgers refers to properties that relate the order in which transactions are sent or received to the order in which they are eventually finalized, i.e…
Towards Secure and Trusted-by-Design Smart Contracts
Zaynah Dargaye, Önder Gürcan, Florent Kirchner +1
Distributed immutable ledgers, or blockchains, allow the secure digitization of evidential transactions without relying on a trusted third-party. Evidential transactions involve th…
Pluralize: a Trustworthy Framework for High-Level Smart Contract-Draft
Zaynah Dargaye, Antonella Pozzo, Sara Tucci-Piergiovanni
The paper presents Pluralize a formal logical framework able to extend the execution of blockchain transactions to events coming from external oracles, like external time, sensor d…