Deep learning-driven defense strategies for mitigating DDoS attacks in cloud computing environments
The kind of cyber threat prevalent and most dangerous to networked systems is the Distributed Denial of Service (DDoS), especially with expanded connection of Internet of Things (IoT) devices. This article categorizes DDoS attacks into three primary types: volumetric, protocol based and application...
Saved in:
Main Authors: | Doaa Mohsin Abd Ali Afraji, Jaime Lloret, Lourdes Peñalver |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2025-12-01
|
Series: | Cyber Security and Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2772918425000025 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data
by: Arjun Kumar Bose Arnob, et al.
Published: (2025-02-01) -
Comprehensive Analysis of DDoS Anomaly Detection in Software-Defined Networks
by: Abdinasir Hirsi, et al.
Published: (2025-01-01) -
A Metaheuristic Approach to Detecting and Mitigating DDoS Attacks in Blockchain-Integrated Deep Learning Models for IoT Applications
by: Manal Alkhammash
Published: (2024-01-01) -
Federated Learning for Decentralized DDoS Attack Detection in IoT Networks
by: Yaser Alhasawi, et al.
Published: (2024-01-01) -
TCN-Based DDoS Detection and Mitigation in 5G Healthcare-IoT: A Frequency Monitoring and Dynamic Threshold Approach
by: Mirza Akhi, et al.
Published: (2025-01-01)