A review on statistical approaches for anomaly detection in DDoS attacks

Author:

Nooribakhsh Mahsa1,Mollamotalebi Mahdi1

Affiliation:

1. Department of Computer, Buinzahra branch, Islamic Azad University, Buinzahra, Iran

Publisher

Informa UK Limited

Subject

Information Systems and Management,Computer Science Applications,Software

Cited by 35 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. Actively Detecting Multiscale Flooding Attacks & Attack Volumes in Resource-Constrained ICPS;IEEE Transactions on Industrial Informatics;2024-07

2. ZF-DDOS: An Enhanced Statistical-Based DDoS Detection Approach using Integrated Z-Score and Fast-Entropy Measures;2024 6th International Conference on Computing and Informatics (ICCI);2024-03-06

3. Time‐based DDoS attack detection through hybrid LSTM‐CNN model architectures: An investigation of many‐to‐one and many‐to‐many approaches;Concurrency and Computation: Practice and Experience;2024-02-14

4. A Hybrid Ensemble Machine Learning Approach (EHML) for DDOS Attack Detection in Smart City Network Traffic;Intelligent Systems for Smart Cities;2024

5. 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

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