Reproduce “ZT-DAC: ML-Driven Dynamic Access Control Policy for Zero Trust in DER Networks” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Arun B. Chandrasekaran, Damilola Popoola, Souradeep Bhattacharya, Manimaran Govindarasu
ZT-DAC combines deterministic role-based policy checks with a learned trust estimate, rechecking trust during sessions. It evaluates the layers separately on 5,248 synthetic DER access requests. OPA achieves 91.92% accuracy and 14.44% FPR; ML-ABAC achieves 93.27% accuracy, 3.88% FPR, and 10.73% FNR. These are separate layer results, not performance measurements for the combined policy.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.