The AI Accountability Infrastructure (AAI) is proposed, centered on a formally defined, hash-chained, digitally signed AI Accountability Record (AAR) and a graduated, threshold-cryptography-enforced disclosure model in which no single party — including the AI provider — holds unilateral access to evidentiary content.
This work presents Mandato, a governance proxy that enforces digitally signed mandates on agent actions at the protocol level, and gives the mandate model and its decision semantics, the reference architecture as an MCP-transparent proxy with separated decision and enforcement points, and a mapping of the mechanism ont...
This work develops Publication Authority as an exact-state, non-transferable, single-use publication capability and instantiate it in PAC-2026 (Publication-Accountability Calculus), a machine-readable AIJIM Protocol candidate, and evaluates its fourth bounded semantic freeze (SF-4), a fixed-profile specification design...
Torsten Tiltack, Yi-Fei Dong, Kun Yu et al.· 0 citations
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 a...
Murali Krishna Pasupuleti· International Journal of Aca...· 0 citations
Security analysis demonstrates that SecuAudit can effectively resist data forgery, metadata tampering, and sub-threshold collusion attacks under the defined threat model, and establishes a feasible framework for secure data circulation under the evaluated deployment assumptions.
Yufa Shi, Jia-Xing Hu, Li-Peng Wang et al.· Computers, Materials & C...· 0 citations
Agentic AI systems increasingly act via tools, memory, delegation, and external services. Existing observability and provenance mechanisms can reconstruct events post hoc, but they rarely show, at the time of the record, whether each policy-relevant action was checked by the intended control before execution. This leav...
Guy Lupo, Nguyen Hung Nguyen, V. Vo et al.· 0 citations
Despite the widespread use of Large Language Models (LLMs) in financial risk control, their opaque reasoning and Retrieval-Augmented Generation (RAG) privacy risks pose severe compliance challenges. While blockchain technology is increasingly adopted to provide tamper-proof auditing for AI decisions, its prohibitive an...
Qi-Qi Feng, Ke-Jie Zhao, Wen-Kai Zhang et al.· International Conference on...· 0 citations
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