Conceptio › Archive › Springer Nature OA
Springer Nature OA open access CC BY 4.0

A deep generative adversarial framework with rat-optimized feature selection for efficient intrusion detection in large-scale cloud network traffic environments

Priya, S. et al.
Springer Nature OA · Papers · License: CC BY 4.0
Open Source ↗
computer-sciencedata-mining-and-knowledge-discoverynatural-language-processing-nlppattern-recognition
Cloud computing is a fundamental paradigm in modern computing; however, its distributed and multi-tenant nature increases exposure to cyber threats, making effective intrusion detection essential. Despite recent advances in artificial intelligence–based intrusion detection systems (IDS), many existi
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

Record · ID 1241723
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