The paper introduces a new benchmark and decomposition method, Sufficiency-Tightness Decomposition, demonstrating that current coding agents struggle to accurately infer least-privilege authorization,…

The paper validates a specialized mathematical metric (the Burau-Lyapunov exponent) designed for detecting privilege escalation in cloud IAM graphs by applying it to an unrelated physical system: sola…

The paper proposes a compositional governance framework to provide richer, dynamic authorization semantics necessary for governing autonomous agentic AI systems, moving beyond traditional static IAM m…

The paper proposes Sovereign 2.0, a control-plane-centric model redefining cloud sovereignty as enforceable governance authority and operational control, rather than mere data location.

The paper introduces a certified purity architecture that strengthens governance in cognitive workflow systems by replacing insufficient runtime checks with cryptographically attested structural guara…

The paper introduces an open-source security framework that significantly improves cloud infrastructure security assessment by unifying identity and resource data, reducing false positives, and automa…

The paper defines AI Identity as the correspondence between an agent's declared state and its observed behavior, concluding that current infrastructure and standards are fundamentally inadequate for g…

ALPS is an automated, vendor-agnostic framework that enforces least privilege in serverless functions by analyzing code and generating precise security policies, achieving high coverage and significan…

The paper develops a formal theory to analyze how throughput changes in AI-enhanced cybersecurity pipelines when stage capacities are perturbed by multipliers.

The paper proposes a portable authorization standard for autonomous agents, addressing the structural gaps in existing identity models when agents operate across organizational boundaries.

The paper introduces the Sovereign Context Protocol (SCP), an open-source, attribution-aware data access layer designed to standardize how Large Language Models (LLMs) connect to and track usage of hu…

The paper proposes a declarative, autonomous, self-protecting framework for securing complex 5G/6G networks by leveraging a standardized security ontology and automated graph reasoning to neutralize l…

The paper proposes n-VM, a novel Layer-1 architecture that unifies multiple heterogeneous virtual machines (VMs) onto a shared consensus and state layer, solving cross-chain fragmentation issues.

The paper proposes Federated Computing as Code (FCaC), a declarative architecture that enforces sovereignty-critical constraints in federated systems by compiling authority into cryptographically veri…

This paper introduces EXTree, a novel structure for Attribute-based Access Control (ABAC) policies that optimizes for both fast evaluation and human-understandable explanations when access is denied.

The paper introduces MolTrust, a production-deployed trust infrastructure built on W3C standards (VCs and DIDs) that provides a verifiable, multi-layered authorization framework for autonomous AI agen…

The paper proves that standard account-based ledgers cannot non-custodially enforce asset disposition, and introduces a novel commitment-based ledger structure, the 'envelope,' that achieves this capa…

This paper proposes an explainable threat attribution system for IoT networks that uses SHAP and flow behavior modeling to accurately classify and explain over 30 distinct attack variants into 8 meani…

The paper proposes using geometric metrics, specifically eigenspace alignment, to monitor the structural integrity of large behavioral populations, demonstrating its effectiveness in detecting network…

The paper introduces Compositional Semantic Fingerprinting (CSF), a black-box method that allows IP owners to attribute fine-tuned text-to-image models to their protected lineages using only query acc…