Bilateral Protection for Private LoRA Inference with Intel TDX
Xiaodong Li, Mingyuan Ma, Dongbo Yan
Cloud services using private low-rank adaptation (LoRA) must protect client inputs and outputs alongside owners' proprietary parameters and execute the approved adaptation. We design and implement a system for bilateral protection of private LoRA inference using Intel Trust Domain Extensions (TDX), connecting approved application identity to actual artifact consumption and adapter activation. The client and LoRA owner independently verify remote attestation, application identity, and binding to the actual Transport Layer Security (TLS) public key before releasing inputs and the weight-decryption key. A fixed read-only image and verified-byte consumption connect approved identities to inference objects, with all inference inside a trust domain. Experiments on real TDX hardware reject controlled application and boot-parameter modifications before secret release. Across 400 fixed dialogues, protected and native CPU inference in the same trust domain produce identical token sequences for all 400 pairs. Across 12 independent trust-domain boots, the steady-state service-to-native time ratio is 1.0094, with a 95% interval of [1.0064, 1.0126]. The system connects bilateral secret release, approved model use, and task-capability preservation, providing verifiable implementation and cost evidence for confidential inference with a public base and private adapter.
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