Springer Nature OA
open access
CC BY-NC-ND 4.0
Enhanced cybersecurity solution via distributed denial of service attack recognition and attribute subset selection
In the cybersecurity domain, a drastic increase in threats affects the security of network and users. Particularly, Distributed Denial of Service (DDoS) attack poses a challenging issue because of its ability to inundate and debilitate targeted systems via distributed networks. Recently, deep learni
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
- Improving cyber-attack detection in Internet of Medical Things using ensemble deep learning methods#340096
- Advanced Persistent Threats in Cybersecurity – Cyber Warfare#98079
- Deep Reinforcement Learning for Intrusion Detection and Response in Software-Defined Networks / Trung Phan Van ; Gutachter: Thomas Bauschert, Rahamatullah Khondoker ; Betreuer: Thomas Bauschert#1145575
- DoS and DDoS attacks in Software Defined Networks: A survey of existing solutions and research challenges#470978
- MTD-Playground: An Attacker-Aware Evaluation Framework for Network Moving Target Defense#792787
Record · ID 1159931
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