KYA provides a framework-agnostic trust layer using inbound pipelines, policy composition, unified trust scoring, interaction multipliers, and delegation attribution to ensure authorized, conforming, and verifiable actions in autonomous systems.
Cryptographic Runtime Governance for Au- tonomous AI Systems: The Aegis Architecture for Verifiable Policy Enforcement,
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
EHV integrates GCD, causal graph CRDTs, TEE attestation, and bounded TLA+ verification to achieve O(1) runtime policy enforcement for agentic AI systems.
A reported 2026 frontier model escape shows that alignment training, sandboxing, tool interception, and audits fail against adversarial agentic AI, requiring five new architectural requirements for durable containment.
citing papers explorer
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KYA: A Framework-Agnostic Trust Layer for Autonomous Systems with Verifiable Provenance and Hierarchical Policy Composition
KYA provides a framework-agnostic trust layer using inbound pipelines, policy composition, unified trust scoring, interaction multipliers, and delegation attribution to ensure authorized, conforming, and verifiable actions in autonomous systems.
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When the Agent Is the Adversary: Architectural Requirements for Agentic AI Containment After the April 2026 Frontier Model Escape
A reported 2026 frontier model escape shows that alignment training, sandboxing, tool interception, and audits fail against adversarial agentic AI, requiring five new architectural requirements for durable containment.