Machine-Verifiable Legal Transactions and Quantum-Secure Cryptographic Agility for Trusted AI-Native 6G Digital Infrastructure

Abstract

Abstract AI-native sixth-generation (6G) infrastructure will increasingly execute network, commercial and public-service actions through autonomous agents distributed across terminals, edges and clouds. Yet a conventional digital signature can authenticate a message without proving that the message was produced under an authorized legal rule, an admissible machine decision, a valid model state, or a quantum-resilient cryptographic configuration. This paper develops a model-based architecture for machine-verifiable legal transactions coupled with cryptographic agility in AI-native 6G environments. The proposed MVLT-QSA6G framework represents legal obligations as signed policy graphs; binds AI decisions to verifiable inference evidence and network context; selects post-quantum or hybrid cryptographic suites through an agility orchestrator; and commits execution evidence to a tamper-evident audit graph. The methodology synthesizes the supplied literature on verifiable AI, post-quantum cryptography, AI-native 6G, terminal-edge-cloud orchestration, secure edge systems and autonomous contract law, then formalizes system trust through weighted state vectors, transition dynamics, constrained optimization and risk-adjusted outcome functions. An illustrative 0–10 numerical model produces a composite trust score of 8.24/10 under the stated assumptions, with sensitivity analysis showing that cryptographic agility becomes increasingly consequential when legal verifiability and AI-proof integrity are already high. The paper contributes a unified technical and conceptual bridge between legal computability, AI assurance, cryptographic migration and 6G control. It further provides an invention-oriented disclosure comprising a technical problem, novel architecture, implementation logic, one independent system claim concept, one independent method claim concept and dependent claim concepts. The contribution is intended as a research and engineering specification requiring empirical, standards-based and jurisdiction-specific validation before operational deployment or patent prosecution. Keywords: machine-verifiable legal transactions; AI-native 6G; post-quantum cryptography; cryptographic agility; verifiable AI; proof of inference; legal policy graphs; terminal-edge-cloud computing; zero-trust assurance; autonomous agents; evidence graphs; network slicing; compliance automation; quantum-safe infrastructure; trusted digital transactions.