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An autonomous cryptanalysis workflow in which agents generate, test, and refine hypotheses before human review is presented, in which reproducible candidates with exact witnesses, controls, code, and run records are returned.
IO Factory, an AI-driven framework for simulating information and influence campaigns as fully integrated, traceable processes, is introduced and shows that IO Factory executes campaign timelines at scale and produces inspectable evidence of exposure and measured movement in configured belief variables.
It is shown that the CRT-FHE scheme of Pradhan et al. is insecure for laws within its assumed error distribution range, and that the transformation from ordinary Ring-LWE to CRT-RLWE does not preserve the error distribution, so it does not establish that CRT-RLWE is at least as hard as Ring-LWE.
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