Entropy and Divergence-based DDoS Attack Detection System in IoT Networks
Author:
Affiliation:
1. University of Regina,Faculty of Engineering and Applied Science,Regina,SK,Canada,S4S 0A2
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10187718/10187720/10187726.pdf?arnumber=10187726
Reference22 articles.
1. A Statistical Approach for Detection of Denial of Service Attacks in Computer Networks
2. CorrAUC: A Malicious Bot-IoT Traffic Detection Method in IoT Network Using Machine-Learning Techniques
3. The detection method of low-rate DoS attack based on multi-feature fusion
4. Comprehensive Review of Artificial Intelligence and Statistical Approaches in Distributed Denial of Service Attack and Defense Methods
5. An Extensible Host-Agnostic Framework for SDN-Assisted DDoS-Mitigation
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1. Optimized Ensemble Model with Genetic Algorithm for DDoS Attack Detection in IoT Networks;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09
2. Exploring Methods of Mitigation against DDoS Attack in an IoT Network;2024 International Conference on Inventive Computation Technologies (ICICT);2024-04-24
3. A Genetic Algorithm- and t-Test-Based System for DDoS Attack Detection in IoT Networks;IEEE Access;2024
4. A Review of Detecting DDoS Attacks Based on Entropy Computation;2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART);2023-12-22
5. Flow and unified information-based DDoS attack detection system for multi-topology IoT networks;Internet of Things;2023-12
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