ArticleFrontiers in artificial intelligence2026
The Agentic AI Framework (AAIF): a policy-enforced architecture for accountable and high-performance intrusion detection.
Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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- Editorial: Advanced integration of large language models for autonomous systems and critical decision support.Frontiers in artificial intelligence · 2026Article
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Abstract
Artificial intelligence plays a central role in modern cybersecurity, yet systems optimized for detection accuracy often lack mechanisms for accountability, transparency, and policy compliance. This study proposes the Agentic AI Framework (AAIF), a policy-aware intrusion detection architecture that integrates predictive modeling with executable governance. Guided by Design Science Research, the framework combines a deep learning detection model with a governance layer aligned to the NIST AI Risk Management Framework 2.0. A key component is an interpretable Policy Engine that enforces operational and ethical constraints through a declarative YAML-based domain-specific language, ensuring that each decision is auditable and policy-compliant. The framework was evaluated on the CICIDS2017 dataset, which contains over 2.8 million network flow records across benign and malicious traffic. Results show that AAIF preserves predictive performance relative to baseline models, including Random Forest, Support Vector Machine, and Deep Neural Network, achieving a weighted
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