Secure Neural Network Inference as a Service with Resource-Constrained Clients

Author:

de Vries Rik1ORCID,Mann Zoltán Ádám1ORCID

Affiliation:

1. University of Amsterdam, Amsterdam, The Netherlands

Publisher

ACM

Reference35 articles.

1. Review of deep learning: concepts, CNN architectures, challenges, applications, future directions;Alzubaidi Laith;Journal of Big Data,2021

2. Dhouha Ayed, Paul-Andrei Dragan, Edith Félix, Zoltán Adám Mann, Eliot Salant, Robert Seidl, Anestis Sidiropoulos, Steve Taylor, and Ricardo Vitorino. 2022. Protecting sensitive data in the cloud-to-edge continuum: The FogProtect approach. In 22nd International Symposium on Cluster, Cloud and Internet Computing (CCGrid). IEEE, 279--288.

3. Co-Design, Development, and Evaluation of a Health Monitoring Tool Using Smartwatch Data: A Proof-of-Concept Study

4. A privacy-preserving protocol for neural-network-based computation

5. Neural networks and their applications

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1. Predicting the Execution Time of Secure Neural Network Inference;IFIP Advances in Information and Communication Technology;2024

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