ACE: An AI-Orchestrated Intrusion Detection and Compliance Mapping Engine
ACE couples Suricata-based intrusion detection with AI-driven regulatory control mapping and automated response, aiming to close the gap between real-time detection and compliance evidence generation.
Summary written by editorial AI · Source link below
arXiv:2610.22702v1 Announce Type: new Abstract: This study proposes the Automated Compliance Engine (ACE), an AI-orchestrated framework that links intrusion detection, regulatory control mapping, and automated countermeasure deployment for security operations environments. ACE integrates Suricata IDS, a LangGraph five-stage workflow, retrieval-augmented generation, NIST SP 800-53 Rev. 5 control retrieval, large language model-based control ranking, and SSH-based Suricata rule deployment. The fr
Editorial Analysis
Bridging the gap between IDS alerts and compliance documentation is a persistent pain point; an AI-orchestrated engine could significantly reduce SOC-to-audit handoff friction.
Assess whether integrating compliance-mapping automation into your SIEM/IDS pipeline would reduce manual regulatory reporting effort.
An AI engine that auto-maps intrusion alerts to regulatory controls could accelerate compliance evidence generation under NIS2 and DORA.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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