Intel HEXL
Author:
Affiliation:
1. Intel Corporation, Santa Clara, CA, USA
2. Intel Corporation, Hillsboro, OR, USA
3. Intel Corporation, Folsom, CA, USA
4. Intel Corporation, Hudson, MA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3474366.3486926
Reference21 articles.
1. Homomorphic Training of 30,000 Logistic Regression Models
2. Secure large-scale genome-wide association studies using homomorphic encryption
3. (Leveled) Fully Homomorphic Encryption without Bootstrapping
4. Homomorphic Encryption for Arithmetic of Approximate Numbers
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1. Efficiency Optimization Techniques in Privacy-Preserving Federated Learning With Homomorphic Encryption: A Brief Survey;IEEE Internet of Things Journal;2024-07-15
2. FHEDA: Efficient Circuit Synthesis with Reduced Bootstrapping for Torus FHE;2024 IEEE 9th European Symposium on Security and Privacy (EuroS&P);2024-07-08
3. SoK: Fully Homomorphic Encryption Accelerators;ACM Computing Surveys;2024-07-05
4. Flagger: Cooperative Acceleration for Large-Scale Cross-Silo Federated Learning Aggregation;2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA);2024-06-29
5. YuX: Finite Field Multiplication Based Block Ciphers for Efficient FHE Evaluation;IEEE Transactions on Information Theory;2024-05
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