GRAIL achieves over 79 times lower latency than LLM-parsing baselines and higher Recall@10 than vector search by combining SLM-enhanced prediction, pseudo-document expansion, and MaxSim resonance on the new AgentTaxo-9K dataset of 9,240 agents.
A novel zero-trust identity framework for agentic AI: Decentralized authentication and fine-grained access control
5 Pith papers cite this work. Polarity classification is still indexing.
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AgentReputation proposes separating AI agent task execution, reputation management, and secure record-keeping into distinct layers, with context-specific reputation cards and a risk-based policy engine to handle verification in decentralized settings.
AgentDID is a W3C-compliant decentralized identity system for AI agents enabling self-managed authentication and state verification via challenge-response.
AI agents require new identity frameworks because fundamental differences from humans in substrate, persistence, verifiability, and legal standing create five unresolved structural gaps in verification, delegation, integrity, governance, and sustainability.
The paper introduces the AI-Identity Risk Taxonomy (AIRT) with 37 risk categories and the Machine Identity Governance Taxonomy (MIGT) as a six-domain framework to close gaps in technical, regulatory, and cross-jurisdictional governance of AI machine identities.
citing papers explorer
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GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing
GRAIL achieves over 79 times lower latency than LLM-parsing baselines and higher Recall@10 than vector search by combining SLM-enhanced prediction, pseudo-document expansion, and MaxSim resonance on the new AgentTaxo-9K dataset of 9,240 agents.
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AgentReputation: A Decentralized Agentic AI Reputation Framework
AgentReputation proposes separating AI agent task execution, reputation management, and secure record-keeping into distinct layers, with context-specific reputation cards and a risk-based policy engine to handle verification in decentralized settings.
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AgentDID: Trustless Identity Authentication for AI Agents
AgentDID is a W3C-compliant decentralized identity system for AI agents enabling self-managed authentication and state verification via challenge-response.
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AI Identity: Standards, Gaps, and Research Directions for AI Agents
AI agents require new identity frameworks because fundamental differences from humans in substrate, persistence, verifiability, and legal standing create five unresolved structural gaps in verification, delegation, integrity, governance, and sustainability.
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Who Governs the Machine? A Machine Identity Governance Taxonomy (MIGT) for AI Systems Operating Across Enterprise and Geopolitical Boundaries
The paper introduces the AI-Identity Risk Taxonomy (AIRT) with 37 risk categories and the Machine Identity Governance Taxonomy (MIGT) as a six-domain framework to close gaps in technical, regulatory, and cross-jurisdictional governance of AI machine identities.