{"ID":2862860,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.26393","arxiv_id":"2509.26393","title":"Exact Bias of Linear TRNG Correctors -- Spectral Approach","abstract":"Using Fourier analysis, this paper establishes near-optimal security bounds for linear correctors commonly used in True Random Number Generators (TRNGs), expressed through code weight enumerators and input bias parameters. We provide the first near-tight bias characterization in total variation, by interpolating between optimal $\\ell_\\infty$ and $\\ell_2$ norm results. Our bounds improve security assessments by an order of magnitude over previously known (overly conservative) estimates. Across $\\sim $20,000 codes, we examine fundamental trade-offs between compression efficiency, cryptographic security, and hardware complexity. Achieving 80-bit security with 10\\% input bias typically requires sacrificing more than 50\\% of the code rate and incurs increased hardware cost. This quantifies the inherent cost of randomness extraction in hardware TRNG implementations.","short_abstract":"Using Fourier analysis, this paper establishes near-optimal security bounds for linear correctors commonly used in True Random Number Generators (TRNGs), expressed through code weight enumerators and input bias parameters. We provide the first near-tight bias characterization in total variation, by interpolating betwee...","url_abs":"https://arxiv.org/abs/2509.26393","url_pdf":"https://arxiv.org/pdf/2509.26393v2","authors":"[\"Maciej Skorski\",\"Francisco-Javier Soto\",\"Onur Günlü\"]","published":"2025-09-30T15:27:43Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.IT\"]","methods":"[]","has_code":false}