34 citations · 74 across the 14 of their papers we have counts for
15 papers
Empirical Analysis of TEE-Enabled Rollup Designs
Claudiu-Nicu Bărbieru, Corentin Libert, Peterson Yuhala +7
Layer 2 (L2) rollups have become the dominant scaling solution in Ethereum. At the core of these systems lies the rollup sequencer, a component that orders, executes, and submits L…
TriHaRd: Higher Resilience for TEE Trusted Time
Matthieu Bettinger, Sonia Ben Mokhtar, Pascal Felber +3
Accurately measuring time passing is critical for many applications. However, in Trusted Execution Environments (TEEs) such as Intel SGX, the time source is outside the Trusted Com…
IM-PIR: In-Memory Private Information Retrieval
Mpoki Mwaisela, Peterson Yuhala, Pascal Felber +1
Private information retrieval (PIR) is a cryptographic primitive that allows a client to securely query one or multiple servers without revealing their specific interests. In spite…
ScamDetect: Towards a Robust, Agnostic Framework to Uncover Threats in Smart Contracts
Pasquale De Rosa, Pascal Felber, Valerio Schiavoni
Smart contracts have transformed decentralized finance by enabling programmable, trustless transactions. However, their widespread adoption and growing financial significance have…
PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
Pasquale De Rosa, Simon Queyrut, Yérom-David Bromberg +2
The Ethereum Virtual Machine (EVM) is a decentralized computing engine. It enables the Ethereum blockchain to execute smart contracts and decentralized applications (dApps). The in…
Practical Secure Aggregation by Combining Cryptography and Trusted Execution Environments
Romain de Laage, Peterson Yuhala, François-Xavier Wicht +3
Secure aggregation enables a group of mutually distrustful parties, each holding private inputs, to collaboratively compute an aggregate value while preserving the privacy of their…
Evaluating the Potential of In-Memory Processing to Accelerate Homomorphic Encryption
Mpoki Mwaisela, Joel Hari, Peterson Yuhala +3
The widespread adoption of cloud-based solutions introduces privacy and security concerns. Techniques such as homomorphic encryption (HE) mitigate this problem by allowing computat…
On the Cost of Model-Serving Frameworks: An Experimental Evaluation
Pasquale De Rosa, Yérom-David Bromberg, Pascal Felber +2
In machine learning (ML), the inference phase is the process of applying pre-trained models to new, unseen data with the objective of making predictions. During the inference phase…
BlindexTEE: A Blind Index Approach towards TEE-supported End-to-end Encrypted DBMS
Louis Vialar, Jämes Ménétrey, Valerio Schiavoni +1
Using cloud-based applications comes with privacy implications, as the end-user looses control over their data. While encrypting all data on the client is possible, it largely redu…
CryptoAnalytics: Cryptocoins Price Forecasting with Machine Learning Techniques
Pasquale De Rosa, Pascal Felber, Valerio Schiavoni
This paper introduces CryptoAnalytics, a software toolkit for cryptocoins price forecasting with machine learning (ML) techniques. Cryptocoins are tradable digital assets exchanged…
Fortress: Securing IoT Peripherals with Trusted Execution Environments
Peterson Yuhala, Jämes Ménétrey, Pascal Felber +2
With the increasing popularity of Internet of Things (IoT) devices, securing sensitive user data has emerged as a major challenge. These devices often collect confidential informat…
A Comprehensive Trusted Runtime for WebAssembly with Intel SGX
Jämes Ménétrey, Marcelo Pasin, Pascal Felber +4
In real-world scenarios, trusted execution environments (TEEs) frequently host applications that lack the trust of the infrastructure provider, as well as data owners who have spec…
A Holistic Approach for Trustworthy Distributed Systems with WebAssembly and TEEs
Jämes Ménétrey, Aeneas Grüter, Peterson Yuhala +4
Publish/subscribe systems play a key role in enabling communication between numerous devices in distributed and large-scale architectures. While widely adopted, securing such syste…
SecV: Secure Code Partitioning via Multi-Language Secure Values
Peterson Yuhala, Pascal Felber, Hugo Guiroux +4
Trusted execution environments like Intel SGX provide \emph{enclaves}, which offer strong security guarantees for applications. Running entire applications inside enclaves is possi…
Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments
Simon Queyrut, Valerio Schiavoni, Pascal Felber
The main premise of federated learning (FL) is that machine learning model updates are computed locally to preserve user data privacy. This approach avoids by design user data to e…