Peer-reviewedCC BY-NC-ND 4.0Scientific Reports
Concurrency aware artificial intelligence for real-time intrusion detection in software-defined networks
Related
- Enhancing Medical Students' Disease Detection Skills: Leveraging Artificial Intelligence Software for Diagnosing Developmental Dysplasia Using Ultrasound Imaging.
- Adaptive active learning and metaheuristic-optimized transformer framework for robust intrusion detection in software-defined networks
- Artificial Intelligence in Common Operating Picture Software for Early Warning and Emergency Management Systems
- PACS-Integrated Artificial Intelligence-Based Software Tool for Rapid and Fully Automatic Bone Fracture Assessment of the Tibial Plateau
- Educational Artificial Intelligence Software to Support Assessment of Atopic Dermatitis Severity
BibTeX
@article{kanimozhi2026concurrency,
title = {{Concurrency aware artificial intelligence for real-time intrusion detection in software-defined networks}},
author = {R. Kanimozhi and V. Padmavathi and M. Latha},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-75362-x},
url = {https://www.nature.com/articles/s41598-026-75362-x},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Concurrency aware artificial intelligence for real-time intrusion detection in software-defined networks
AU - R. Kanimozhi
AU - V. Padmavathi
AU - M. Latha
PY - 2026
DA - 2026/10/21
JO - Scientific Reports
DO - 10.1038/s41598-026-75362-x
UR - https://www.nature.com/articles/s41598-026-75362-x
SN - 2045-2322
ER -