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Adaptive Authentication Framework for Agentic AI Ecosystems: Protocol Design, Trust Evaluation, and Security Analysis

https://doi.org/10.55640/ijctisn-v03i09-05

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Haruto Nakamura ¹ , Yui Takahashi ¹ ,

⁴ AI Research Scientist, Japan

⁴ Intelligent Systems Research Analyst, Japan

Abstract

The emergence of agentic artificial intelligence (AI) introduces authentication requirements that differ substantially from those of conventional user-centric computing systems. Autonomous agents can initiate actions, invoke tools, exchange information with other agents, operate across heterogeneous environments, and continuously modify their behavior according to contextual objectives. Consequently, authentication mechanisms based exclusively on static identity credentials are insufficient for establishing persistent confidence in an agent's legitimacy and operational trustworthiness. This paper proposes an Adaptive Authentication Framework for Agentic AI Ecosystems that integrates protocol-aware identity verification, contextual trust evaluation, adaptive authentication decisions, and continuous security analysis. The framework is theoretically grounded in the conceptual authentication requirements of agentic AI ecosystems and further draws an analytical analogy from stability-oriented feature-selection research, where reliable decisions depend on identifying robust signals across changing conditions. The proposed methodology models authentication as a continuous decision process rather than a one-time identity check. It introduces four principal stages: identity establishment, protocol validation, contextual trust assessment, and adaptive authentication enforcement. A hypothetical evaluation demonstrates how authentication strength can be dynamically increased when agents exhibit anomalous behavior, interact with unfamiliar resources, or operate under elevated risk. The analysis indicates that adaptive authentication can reduce dependence on static credentials while improving resilience against identity spoofing, compromised agents, contextual manipulation, and unstable trust signals. The principal contribution is a conceptual architecture that connects protocol-level authentication with continuously evaluated trust, thereby providing a foundation for secure autonomous-agent ecosystems.

Keywords

Agentic AI, Adaptive Authentication, AI Agents, Trust Evaluation

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