machine learning and deep learning techniques for distributed denial of service anomaly detection in software defined networks—current research solutions

NS Musa, NM Mirza, SH Rafique, AM Abdallah… - IEEE …, 2024 - ieeexplore.ieee.org
This state-of-the-art review comprehensively examines the landscape of Distributed Denial
of Service (DDoS) anomaly detection in Software Defined Networks (SDNs) through the lens …

A comprehensive survey on low-rate and high-rate DDoS defense approaches in SDN: taxonomy, research challenges, and opportunities

S Karnani, N Agrawal, R Kumar - Multimedia Tools and applications, 2024 - Springer
Abstract Software Defined Networking (SDN) expands the networking capabilities using
abstraction, open-source protocols, energy efficiency, and programmable features for …

Heuristic machine learning approaches for identifying phishing threats across web and email platforms

R Jayaprakash, K Natarajan, JA Daniel… - Frontiers in Artificial …, 2024 - frontiersin.org
Life has become more comfortable in the era of advanced technology in this cutthroat
competitive world. However, there are also emerging harmful technologies that pose a …

Identification and mitigation of phishing email attacks using deep learning

J Ramprasath, S Priyanka, R Manudev… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Internet security is seriously threatened by email-based internet phishing. The process of
completely hiding the sender information of a phishing mails is far less flexible than the …

Hybridization of synergistic swarm and differential evolution with graph convolutional network for distributed denial of service detection and mitigation in IoT …

CR Babu, M Suneetha, MA Ahmed, PR Babu… - Scientific Reports, 2024 - nature.com
Enhanced technologies of the future are gradually improving the digital landscape. Internet
of Things (IoT) technology is an advanced technique that is quickly increasing owing to the …

Secured data transaction for agriculture harvesting using blockchain technology

J Ramprasath, MM Nishath… - … on Vision Towards …, 2023 - ieeexplore.ieee.org
One of the biggest sectors in the world is agriculture, and a lot of data is produced every day
in this industry. However, because there aren't adequate data management systems, this …

An efficient DDoS attack detection and prevention model using fusion heuristic enhancement of deep learning approach in FANET sector

SP Priyadharshini, P Balamurugan - Applied Soft Computing, 2024 - Elsevier
Abstract Problem overview A Flying Ad-hoc Network (FANET) is a decentralized
communication network formed by Unmanned Aerial Vehicles (UAVs). However, it faces …

Modeling DDOS attacks in sdn and detection using random forest classifier

A Abdullahi Wabi, I Idris, O Mikail Olaniyi… - Journal of Cyber …, 2024 - Taylor & Francis
ABSTRACT A Software-defined network paradigm provides flexibility and programmability to
deal with the growing users of future networks. As a result of the centralized control attribute …

ML-Based Anomaly Detection in 6G Networks: A Survey on the Current Status, Challenges, and Future Directions

N Nezhadsistani, B Stiller - 2024 3rd International Conference …, 2024 - ieeexplore.ieee.org
As the development of 6G networks accelerates, ensuring robust security measures
becomes paramount to safeguard against emerging threats. Anomaly detection, a crucial …

Detection and Prevention of Distributed Denial of Service (DDoS) Attacks Using Machine Learning Techniques

A Varma, AT Kumar, B Yamini - 2024 2nd International …, 2024 - ieeexplore.ieee.org
DDoS attack detection/prevention is vital across industries to thwart data breaches.
Employing tech like data loss prevention systems and fostering security-aware culture …