Advanced security framework for 5G-SDN attack detection and mitigation using Affinity Cohesive Clustering and Improved Chaotic Walrus-Optimized Convolutional LSTM with Deep Dual Info-Varcoder
- DOI
- 10.3389/frai.2026.1832131
- Published
- 2026-09-03
- Container
- Frontiers in Artificial Intelligence
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/frai.2026.1832131,
title = {Advanced security framework for 5G-SDN attack detection and mitigation using Affinity Cohesive Clustering and Improved Chaotic Walrus-Optimized Convolutional LSTM with Deep Dual Info-Varcoder},
author = {Shameli R. and Sujatha Rajkumar},
year = {2026},
journal = {Frontiers in Artificial Intelligence},
doi = {10.3389/frai.2026.1832131},
url = {https://doi.org/10.3389/frai.2026.1832131}
}RIS
TY - JOUR TI - Advanced security framework for 5G-SDN attack detection and mitigation using Affinity Cohesive Clustering and Improved Chaotic Walrus-Optimized Convolutional LSTM with Deep Dual Info-Varcoder AU - Shameli R. AU - Sujatha Rajkumar PY - 2026 JO - Frontiers in Artificial Intelligence DO - 10.3389/frai.2026.1832131 UR - https://doi.org/10.3389/frai.2026.1832131 ER -
APA
R., S., & Rajkumar, S. (2026). Advanced security framework for 5G-SDN attack detection and mitigation using Affinity Cohesive Clustering and Improved Chaotic Walrus-Optimized Convolutional LSTM with Deep Dual Info-Varcoder. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2026.1832131
Source records
- crossref · retrieved 2026-09-25T10:29:10.855Z