AICCE: AI Driven Compliance Checker Engine
Summary: arXiv:2604.03330v1 Announce Type: cross
Abstract: For digital infrastructure to be safe, compatible, and standards-aligned, automated communication protocol compliance verification is crucial. Nevertheless, current rule-based systems are becoming less and less effective since they are unable to identify subtle or intricate non-compliance, which attackers frequently use to establish covert communication channels in IPv6 traffic. In order to automate IPv6 compliance verification, this paper presents the Artificial Intelligence Driven Compliance Checker Engine (AICCE), a novel generative system that combines dual-architecture reasoning and retrieval-augmented generation (RAG).
Overview of AICCE
AICCE utilizes a unique approach to enhance the compliance verification process. By semantically encoding protocol standards into a high-dimensional vector space, the system can efficiently retrieve specification segments that are pertinent to each query. This innovative framework allows AICCE to offer two complementary pipelines:
- Explainability Mode: This mode employs parallel Large Language Model (LLM) agents to render decisions and resolve disputes through organized discussions. This feature significantly improves interpretability and robustness in the decision-making process.
- Script Execution Mode: In this mode, clauses are converted into Python rules that can be executed swiftly for comprehensive dataset verification. This enhances the efficiency of the compliance checking process.
Performance and Effectiveness
AICCE has been rigorously tested on IPv6 packet samples across sixteen cutting-edge generative models. The results demonstrate that AICCE achieves accuracy and F1-scores of up to 99%. The debate mechanism employed in Explainability Mode enhances decision reliability in complex scenarios, while the script-based pipeline reduces per-sample latency.
Advantages of AICCE
The introduction of AICCE marks a significant advancement in the field of compliance verification for digital infrastructures. The key advantages of AICCE include:
- Scalability: AICCE can efficiently handle large datasets, making it suitable for dynamic communication environments.
- Auditability: The system provides a transparent mechanism for compliance checking, allowing for easy audits and reviews.
- Generalizability: AICCE can adapt to various communication protocols, ensuring broad applicability across different systems.
- Enhanced Detection: By overcoming the limitations of traditional rule-based systems, AICCE can identify both routine and covert non-compliance, addressing the blind spots that attackers often exploit.
Conclusion
The Artificial Intelligence Driven Compliance Checker Engine (AICCE) represents a groundbreaking solution to the challenges of automated communication protocol compliance verification. By leveraging advanced AI techniques, AICCE not only enhances the accuracy and efficiency of compliance checking but also opens new avenues for ensuring the security and robustness of digital infrastructures. As the landscape of digital communication continues to evolve, innovations like AICCE will be crucial in maintaining compliance and safeguarding against emerging threats.