FedDDoS: An efficient federated learning-based DDoS attacks classification in SDN-enabled IIoT networks
Independent distribution systems are made possible by Industry 4.0, and these systems
produce heterogeneous data that is vulnerable to cyberattacks. The Distributed Denial of …
produce heterogeneous data that is vulnerable to cyberattacks. The Distributed Denial of …
An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks
Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have
a centralized controller that is a single attractive target for unauthorized users to attack …
a centralized controller that is a single attractive target for unauthorized users to attack …
Federated Learning for Decentralized DDoS Attack Detection in IoT Networks
Y Alhasawi, S Alghamdi - IEEE Access, 2024 - ieeexplore.ieee.org
In the ever-expanding domain of Internet of Things (IoT) networks, Distributed Denial of
Service (DDoS) attacks represent a significant challenge, compromising the reliability of …
Service (DDoS) attacks represent a significant challenge, compromising the reliability of …
[HTML][HTML] Machine learning-based dynamic attribute selection technique for ddos attack classification in iot networks
The exponential growth of the Internet of Things (IoT) has led to the rapid expansion of
interconnected systems, which has also increased the vulnerability of IoT devices to security …
interconnected systems, which has also increased the vulnerability of IoT devices to security …
Ae-mlp: A hybrid deep learning approach for ddos detection and classification
Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet
connectivity massively grows in recent years. Conventional shallow machine learning-based …
connectivity massively grows in recent years. Conventional shallow machine learning-based …
Multi-Level Deep Neural Network for Distributed Denial-of-Service Attack Detection and Classification in Software-Defined Networking Supported Internet of Things …
With the increasing rates of interconnected Internet of Things (IoT) devices within Software-
Defined Networking (SDN) environments, distributed denial of service (DDoS) attacks have …
Defined Networking (SDN) environments, distributed denial of service (DDoS) attacks have …
Ddos attack detection based on cnn and federated learning
D Lv, X Cheng, J Zhang, W Zhang… - … on Advanced Cloud …, 2022 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attack, which seriously affects the availability of the
Internet, is one of the most dangerous network attacks. Machine learning is widely used in …
Internet, is one of the most dangerous network attacks. Machine learning is widely used in …
Developing Realistic Distributed Denial of Service (DDoS) Dataset for Machine Learning-based Intrusion Detection System
During the last decade, attackers have compromised reputable systems to launch massive
Distributed Denial of Services (DDoS) attacks against banking services, corporate websites …
Distributed Denial of Services (DDoS) attacks against banking services, corporate websites …
Towards an optimal feature selection method for AI-based DDoS detection system
S Saha, AT Priyoti, A Sharma… - 2022 IEEE 19th Annual …, 2022 - ieeexplore.ieee.org
Cyber-attacks are increasing rapidly, so developing effective intrusion detection and
prevention tools for a secure and safer cyberspace is crucial. DDoS (Distributed Denial of …
prevention tools for a secure and safer cyberspace is crucial. DDoS (Distributed Denial of …
A framework for ddos attack detection in sdn-based iot using hybrid classifier
Abstract Software Defined Networks (SDN) and Internet of Things (IoT) are the two emerging
fields and due to their ability to provide ease in accessing the information for managing …
fields and due to their ability to provide ease in accessing the information for managing …