[
    {
        "id": "osp-18544",
        "type": "article-journal",
        "title": "Trusted Hardware Acceleration for Malicious-Secure Function Secret Sharing",
        "author": [
            {
                "family": "Xue",
                "given": "Yujie"
            },
            {
                "family": "Peng",
                "given": "Yijing"
            },
            {
                "family": "Liu",
                "given": "Lin"
            },
            {
                "family": "Fu",
                "given": "Shaojing"
            },
            {
                "family": "Li",
                "given": "Shaoqing"
            },
            {
                "family": "Wang",
                "given": "Yaohua"
            },
            {
                "family": "Chen",
                "given": "Rongmao"
            },
            {
                "family": "Guo",
                "given": "Yang"
            }
        ],
        "URL": "https://omanscience.com/en/articles/trusted-hardware-acceleration-for-malicious-secure-function-secret-sharing",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Function secret sharing (FSS) underlies two-party private inference and private information retrieval, with cost dominated by generating, moving and evaluating distributed point function (DPF) keys. A trusted GPU-integrated distributed function accelerator (DFA) removed key movement by generating and consuming keys locally, but tolerates only semi-honest adversaries. A malicious host or GPU can tamper with shares, replay one-time material, swap buffers after checking, request early outputs, or abuse the accelerator as a forgery oracle, while malicious FSS ships large authenticated keys or multiplies DPF work. We present VIGOR-DFA, protecting the chain from authorized input to authorized output release with three mechanisms: a fresh authentication epilogue using three field multiplications per DPF output, 3.8-4.0 times faster per gate than per-lane DPF tag trees; a freeze-before-challenge check of every opening with t = 3 independent MAC lanes over F_{2^61-1}; and a role-bound one-time resource ledger with a release guard, in a protected datapath beside the GPU L2 cache. We prove stand-alone static malicious security with abort in a protected-module model, with statistical error Q(2/p)^t approximately 2^-148 for Q less than or equal to 2^32 checked batches. Our DFA-calibrated model shows that, against dealer-based malicious FSS modeled after the protocol family of Shark, VIGOR-DFA removes 21.8-563 GB of per-query offline authenticated material and, mainly by generating it in-module, lowers LAN latency by 10.1-14.0 times (1.5-1.8 times excluding offline distribution) and energy by 3.0-3.9 times. Malicious security costs 2.5-3.5 times LAN latency over semi-honest DFA and 0.145 mm^2 at 7 nm. We have completed the verification of specifications and the functional CPU reference model, including GPU/RTL conformance verification, protected runtime evaluation, and deployment-related tests."
    }
]