[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
DDoS attack detection techniques in IoT networks: a survey
Abstract The Internet of Things (IoT) is a rapidly emerging technology that has become more
valuable and vital in our daily lives. This technology enables connection and communication …
valuable and vital in our daily lives. This technology enables connection and communication …
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 …
Intrusion detection system on IoT with 5G network using deep learning
The Internet of Things (IoT) cyberattacks of fully integrated servers, applications, and
communications networks are increasing at exponential speed. As problems caused by the …
communications networks are increasing at exponential speed. As problems caused by the …
Low rate DDoS detection using weighted federated learning in SDN control plane in IoT network
The Internet of things (IoT) has opened new dimensions of novel services and computing
power for modern living standards by introducing innovative and smart solutions. Due to the …
power for modern living standards by introducing innovative and smart solutions. Due to the …
Towards effective detection of recent DDoS attacks: A deep learning approach
Distributed Denial of Service (DDoS) is a predominant threat to the availability of online
services due to their size and frequency. However, develo** an effective security …
services due to their size and frequency. However, develo** an effective security …
Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review
Abstract Internet of Things (IoT) driven systems have been sharply growing in the recent
times but this evolution is hampered by cybersecurity threats like spoofing, denial of service …
times but this evolution is hampered by cybersecurity threats like spoofing, denial of service …
[HTML][HTML] Advancing XSS detection in IoT over 5g: a cutting-edge artificial neural network approach
The rapid expansion of the Internet of Things (IoT) and the advancement of 5G technology
require strong cybersecurity measures within IoT frameworks. Traditional security methods …
require strong cybersecurity measures within IoT frameworks. Traditional security methods …
Hybrid deep learning approach for automatic DoS/DDoS attacks detection in software-defined networks
This paper proposes a hybrid deep learning algorithm for detecting and defending against
DoS/DDoS attacks in software-defined networks (SDNs). SDNs are becoming increasingly …
DoS/DDoS attacks in software-defined networks (SDNs). SDNs are becoming increasingly …
DDoS attacks and machine‐learning‐based detection methods: A survey and taxonomy
Distributed denial of service (DDoS) attacks represent a significant cybersecurity challenge,
posing a critical risk to computer networks. Develo** an effective defense mechanism …
posing a critical risk to computer networks. Develo** an effective defense mechanism …