Scaling Homomorphic Applications in Deployment
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Abstract (arXiv)
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
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- 2025SoK: Can Fully Homomorphic Encryption Support General AI Computation? A Functional and Cost Analysis
- 2026CHEHAB RL: Learning to Optimize Fully Homomorphic Encryption Computations
- 2026Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints
- 2026HEAT: Faster Fully Homomorphic Inference via Approximations-Weights Co-Adaptation
- 2023FheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users
- 2025Efficient Implementation of Reinforcement Learning over Homomorphic Encryption
- 2025Design and Optimization of Cloud Native Homomorphic Encryption Workflows for Privacy-Preserving ML Inference
- 2026Public-Decay Homomorphic State Space Models for Private Sequence Inference