Evaluating Behavioral Context for Interpretable IAM Policy Risk Scoring in Cloud Environments

cs.CR, cs.DC, cs.LG, cs.NI

Submitted: 2026-10-05

Updated: 2026-10-05

Comments: 6 pages, 5 figures, 5 tables. Peer-reviewed and accepted at IEEE Conference ID# 71863; to appear in the IEEE Xplore proceedings

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• TAC: Hybrid IAM Privilege Escalation Detection
• Graph Neural Network Based Adaptive Threat Detection for Cloud Identity and Access Management Logs
• InterpretML: A Unified Framework for Machine Learning Interpretability

Related papers

• SoK: AI-Augmented Binary Reversing
• Relaxed Sender Anonymity for CBDC Interbank Settlement: A Zero-Knowledge Approach on Permissioned EVM
• Calibration-Family Overfit: Why Trusted Sabotage Monitors Don't Transfer Across Lineages
• Efficient Fuzzy PSI under One-Sided Assumptions
• Sealing the Audit-Runtime Gap for LLM Skills
• Token Composition: A Graph Based on EVM Logs