Enhancing ML-Based DoS Attack Detection Through Combinatorial Fusion Analysis
Author:
Affiliation:
1. Fordham Univ.,NY,USA
2. Cyber Florida,FL,USA
3. RENCI,NC,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10288629/10288642/10288981.pdf?arnumber=10288981
Reference14 articles.
1. From CIC-IDS2017 to LYCOS-IDS2017: A corrected dataset for better performance
2. Cognitive Diversity: A Measurement of Dissimilarity Between Multiple Scoring Systems
3. A Lightweight Residual Networks Framework for DDoS Attack Classification Based on Federated Learning
4. Multi-Layer Combinatorial Fusion Using Cognitive Diversity
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Redefining DDoS Attack Detection Using A Dual-Space Prototypical Network-Based Approach;2024 33rd International Conference on Computer Communications and Networks (ICCCN);2024-07-29
2. Advancing NCAA March Madness Forecasts Through Deep Learning and Combinatorial Fusion Analysis;Lecture Notes in Networks and Systems;2024
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