arXiv (All)
open access
GreenNIDS: A Benchmark Workflow and Analysis Dataset for NetFlow Intrusion Detection Experiments
Comparing the predictive performance and computational cost of flow-based intrusion detection experiments requires both quantities to be available for each run. GreenNIDS connects benchmark execution on public NetFlow datasets to a reusable analysis dataset. Model implementations write a common set
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
- GreenNIDS: A Benchmark Workflow and Analysis Dataset for NetFlow Intrusion Detection Experiments#1381155
- SERA-IDS: Structured Experience Retrieval-Augmented Intrusion Detection with Small Language Models#1199273
- An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization.#360930
- An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization#355766
- Tool Demo: Topology analysis with GPML for detection of cyberattacks in Water Distribution Networks#432454
Record · ID 1400195
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