Alberto Ibarrondo

Orcid: 0000-0003-4079-4127

According to our database1, Alberto Ibarrondo authored at least 11 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Funshade: Function Secret Sharing for Two-Party Secure Thresholded Distance Evaluation.
Proc. Priv. Enhancing Technol., October, 2023

Privacy-preserving biometric recognition systems with advanced cryptographic techniques. (Systèmes de reconnaissance biométrique préservant la confidentialité bassés sur des techniques cryptographiques avancées).
PhD thesis, 2023

Privacy-preserving Cosine Similarity Computation with Malicious Security Applied to Biometric Authentication.
IACR Cryptol. ePrint Arch., 2023

Grote: Group Testing for Privacy-Preserving Face Identification.
Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy, 2023

2022
Funshade: Functional Secret Sharing for Two-Party Secure Thresholded Distance Evaluation.
IACR Cryptol. ePrint Arch., 2022

Colmade: Collaborative Masking in Auditable Decryption for BFV-based Homomorphic Encryption.
Proceedings of the IH&MMSec '22: ACM Workshop on Information Hiding and Multimedia Security, Santa Barbara, CA, USA, June 27, 2022

2021
Banners: Binarized Neural Networks with Replicated Secret Sharing.
IACR Cryptol. ePrint Arch., 2021

Pyfhel: PYthon For Homomorphic Encryption Libraries.
Proceedings of the WAHC '21: Proceedings of the 9th on Workshop on Encrypted Computing & Applied Homomorphic Cryptography, 2021

Practical Privacy-Preserving Face Identification Based on Function-Hiding Functional Encryption.
Proceedings of the Cryptology and Network Security - 20th International Conference, 2021

2018
Intellectual Property Protection for Distributed Neural Networks - Towards Confidentiality of Data, Model, and Inference.
Proceedings of the 15th International Joint Conference on e-Business and Telecommunications, 2018

FHE-Compatible Batch Normalization for Privacy Preserving Deep Learning.
Proceedings of the Data Privacy Management, Cryptocurrencies and Blockchain Technology, 2018


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