Springer Nature OA
open access
CC BY-NC-ND 4.0
Edge weight concentration overcomes node degree blindness in graph based network intrusion detection
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Blockchain-anchored multi-discriminator GAN architecture for real-time zero-day attack detection in social IoT edge networks with explainable audit trails#613671
- Minimal even sets of nodes#639179
- A resource efficient IoT intrusion detection model using hybrid feature selection for edge computing.#437241
- A resource efficient IoT intrusion detection model using hybrid feature selection for edge computing#431827
- Minimum Vertex Cut with Reachable Set (MVCRS) Problem for Suppressing Botnet Propagation in IoT Networks: Complexity and Algorithms.#143466
Record · ID 660414
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive