34 citations · 74 across the 14 of their papers we have counts for
4 papers · 1 filter
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…