Federated learning for intrusion detection system: Concepts, challenges and future directions

S Agrawal, S Sarkar, O Aouedi, G Yenduri… - Computer …, 2022 - Elsevier
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …

Deep learning approaches for detecting DDoS attacks: A systematic review

M Mittal, K Kumar, S Behal - Soft computing, 2023 - Springer
In today's world, technology has become an inevitable part of human life. In fact, during the
Covid-19 pandemic, everything from the corporate world to educational institutes has shifted …

Distributed denial-of-service (DDoS) attacks and defense mechanisms in various web-enabled computing platforms: issues, challenges, and future research directions

A Singh, BB Gupta - International Journal on Semantic Web and …, 2022 - igi-global.com
The demand for Internet security has escalated in the last two decades because the rapid
proliferation in the number of Internet users has presented attackers with new detrimental …

Machine learning techniques to detect a DDoS attack in SDN: A systematic review

TE Ali, YW Chong, S Manickam - Applied Sciences, 2023 - mdpi.com
The recent advancements in security approaches have significantly increased the ability to
identify and mitigate any type of threat or attack in any network infrastructure, such as a …

A unified deep learning anomaly detection and classification approach for smart grid environments

I Siniosoglou, P Radoglou-Grammatikis… - … on Network and …, 2021 - ieeexplore.ieee.org
The interconnected and heterogeneous nature of the next-generation Electrical Grid (EG),
widely known as Smart Grid (SG), bring severe cybersecurity and privacy risks that can also …

Machine learning approaches for combating distributed denial of service attacks in modern networking environments

A Aljuhani - IEEE Access, 2021 - ieeexplore.ieee.org
A distributed denial of service (DDoS) attack represents a major threat to service providers.
More specifically, a DDoS attack aims to disrupt and deny services to legitimate users by …

An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks

A Zainudin, LAC Ahakonye, R Akter… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
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 …

AI/ML for network security: The emperor has no clothes

AS Jacobs, R Beltiukov, W Willinger… - Proceedings of the …, 2022 - dl.acm.org
Several recent research efforts have proposed Machine Learning (ML)-based solutions that
can detect complex patterns in network traffic for a wide range of network security problems …

Optimization Enabled Deep Learning‐Based DDoS Attack Detection in Cloud Computing

S Balasubramaniam, C Vijesh Joe… - … Journal of Intelligent …, 2023 - Wiley Online Library
Cloud computing is a vast revolution in information technology (IT) that inhibits scalable and
virtualized sources to end users with low infrastructure cost and maintenance. They also …

Implementation of intrusion detection model for DDoS attacks in Lightweight IoT Networks

SA Khanday, H Fatima, N Rakesh - Expert Systems with Applications, 2023 - Elsevier
Protecting IoT networks and infrastructure is one of the top priorities in today's computing
industry because of the unnerving and exponential development in cyberattacks and …