Scaling Homomorphic Applications in Deployment
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911189250867200 |
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| author | Marinelli, Ryan Chowdhury, Angelica |
| author_facet | Marinelli, Ryan Chowdhury, Angelica |
| contents | In this endeavor, a proof-of-concept homomorphic application is developed to determine the production readiness of encryption ecosystems. A movie recommendation app is implemented for this purpose and productionized through containerization and orchestration. By tuning deployment configurations, the computational limitations of Fully Homomorphic Encryption (FHE) are mitigated through additional infrastructure optimizations
Index Terms: Reinforcement Learning, Orchestration, Homomorphic Encryption |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_02376 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scaling Homomorphic Applications in Deployment Marinelli, Ryan Chowdhury, Angelica Cryptography and Security Artificial Intelligence In this endeavor, a proof-of-concept homomorphic application is developed to determine the production readiness of encryption ecosystems. A movie recommendation app is implemented for this purpose and productionized through containerization and orchestration. By tuning deployment configurations, the computational limitations of Fully Homomorphic Encryption (FHE) are mitigated through additional infrastructure optimizations Index Terms: Reinforcement Learning, Orchestration, Homomorphic Encryption |
| title | Scaling Homomorphic Applications in Deployment |
| topic | Cryptography and Security Artificial Intelligence |
| url | https://arxiv.org/abs/2510.02376 |