Private ML SDK provides a secure environment for running LLM workloads with guaranteed privacy and security, preventing unauthorized access to both the model and user data during inference operations.
Abstract: To address the risks of data leakage and unauthorized access in Intelligent Transportation Systems (ITS), particularly in the post-quantum era where traditional cryptographic algorithms are ...
Abstract: This article introduces an ElGamal-based asymmetric updatable encryption scheme, tailored to address the challenges of secure key rotation in cryptographic systems. The proposed solution ...