Abstract
Proposed herein is an artificial intelligence (AI) for information technology operations (AIOps)-driven engine and system that provides for the ability to automate the transition from legacy Internet Protocol (IP)-based rules to identity-centric, zero trust policies. In this context, Security Group Tags (SGTs) are used as an illustrative example of such attribute-based policies. The system correlates identity metadata with real-time traffic telemetry and applies a Stability Index (SI) to evaluate whether a legacy rule can be converted to an attribute-based policy with reduced risk of service disruption. The SI considers identity consistency, temporal persistence, and traffic coverage so that conversion recommendations are based on empirical behavior over an observation window rather than a single static snapshot. The system can provide migration readiness scores, require manual review for probabilistic cases, or recommend that volatile mappings remain IP-based until identity or telemetry issues are resolved.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Morais, Renato, "SYSTEM AND TECHNIQUES TO FACILITATE PROBABILISTIC ATTRIBUTE-BASED SECURITY POLICY CONVERSIONS", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10832