A first multivocal literature review finds academia modifies IoT to meet Zero Trust rules while industry integrates IoT into existing NIST-guided Zero Trust frameworks, exposing gaps in socio-technical and cost-benefit analysis.
Designing an efficient security framework for detecting intrusions in virtual network of cloud computing,
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FOT-CFM generates turbulent fields in function space with superior high-order statistics and energy spectra on Navier-Stokes, Kolmogorov flow, and Hasegawa-Wakatani equations compared to baselines.
MDE computes three entropy features from flow stats to match conventional ML performance (F1 0.708-0.989) on four IDS benchmarks while exposing aggregate-metric failures and providing stable SHAP attributions.
Evidence-based taxonomy of security properties with first-order logic definitions and ProVerif/Tamarin executable examples derived from a 2022-2025 literature review of 53 studies.
MoCQ combines LLMs with symbolic validation to generate vulnerability patterns for static analysis, matching expert performance on 12 types across four languages and finding 25 new real-world vulnerabilities.
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Neuro-symbolic Static Analysis with LLM-generated Vulnerability Patterns
MoCQ combines LLMs with symbolic validation to generate vulnerability patterns for static analysis, matching expert performance on 12 types across four languages and finding 25 new real-world vulnerabilities.