arXiv:2608.17352v1 Announce Type: new Abstract: Distributed Denial-of-Service (DDoS) attacks threaten network availability, requiring a cognitive detection process that senses
arXiv:2606.17109v1 Announce Type: cross Abstract: Given their effectiveness in modeling the relational structure among network traffic flows, graph neural networks (GNNs) have
arXiv:2602.05817v2 Announce Type: cross Abstract: The rapid expansion of Internet of Things (IoT) ecosystems has led to increasingly complex and heterogeneous network topologies.
arXiv:2610.04019v1 Announce Type: new Abstract: Graph based cyber attack detection studies employ various graph construction and representation strategies across different
arXiv:2603.22366v1 Announce Type: cross Abstract: We propose a Quantum Federated Autoencoder for Anomaly Detection, a framework that leverages quantum federated learning for
arXiv:2608.20738v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are widely used on graph-structured data, but most suffer from two key weaknesses. First, message
arXiv:2603.25763v1 Announce Type: cross Abstract: The Internet of Vehicles (IoV) has become an essential component of smart transportation systems, enabling seamless interaction
arXiv:2610.02342v1 Announce Type: new Abstract: Natural Visibility Graph (NVG) based analysis characterizes network traffic through topological descriptors reflecting different
NewsHive monitors these sources continuously. All signal titles above link to the original reporting.
Intelligence by NewsHive. Need help navigating what this means for your business? Contact GeekyBee →