Dynamic Graph Models Detect Anomalies in 5G Networks
Proposes dynamic graph formalism for 5G anomaly detection capturing packet-level content and contexts.
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9 stories, newest first · one card per story
Stories tagged #graph-learning
Spectral braids turn eigenvalue crossings into features for directed networks
Burau features from tracked complex eigenvalues reach 97.1% accuracy on four synthetic classes, versus 44.5% without eigenvalue tracking.
Study finds when trusting graph relations hurts detectors
Clean-trained graph detectors fell below graph-free counterparts in 58 of 90 settings on six graphs.
GraphDecisionBench: Benchmarking System One Models on Graph Tasks
GraphDecide benchmarks Jev and other choice-based models on graph decision tasks.
Degree-Corrected Joint Matrix Factorization for Multilayer Community Detection
A degree-corrected joint matrix factorization detects shared communities across multilayer networks.
HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning
HYDRA uses hierarchical Android app graphs and contrastive learning to adapt malware detectors to concept drift with far fewer labels.
Particle Competition and Cooperation for Robust Graph Convolutional Network Learning Under Label Noise
PCC+GCN refines noisy graph labels before training, slightly beating a baseline GCN with lower runtime.
Not All Relations Are Equal: Relation-Balanced and Calibrated Graph Learning for Provenance-Based Intrusion Detection
RECAL improves provenance-based APT detection with relation-balanced masked graph learning and calibrated errors, reaching 99.99% F1 on DARPA E3 datasets.
A First-Principles Evaluation of Graph-Based Network Intrusion Detection Systems
GIDS-Eval framework reveals evaluation gaps in graph-based network intrusion detection; two crafted edges fully evade three detector-dataset pairs.