Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy

D Soni, N Kumar - Journal of Network and Computer Applications, 2022 - Elsevier
Cloud computing offers Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …

A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking

AA Bahashwan, M Anbar, S Manickam, TA Al-Amiedy… - Sensors, 2023 - mdpi.com
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …

An optimized ensemble prediction model using AutoML based on soft voting classifier for network intrusion detection

MA Khan, N Iqbal, H Jamil, DH Kim - Journal of Network and Computer …, 2023 - Elsevier
Traditional ML based IDS cannot handle high-speed and ever-evolving attacks.
Furthermore, these traditional IDS face several common challenges, such as processing …

A novel ensemble learning-based model for network intrusion detection

N Thockchom, MM Singh, U Nandi - Complex & Intelligent Systems, 2023 - Springer
The growth of Internet and the services provided by it has been growing exponentially in the
past few decades. With such growth, there is also an ever-increasing threat to the security of …

Recognition of DDoS attacks on SD-VANET based on combination of hyperparameter optimization and feature selection

M Türkoğlu, H Polat, C Koçak, O Polat - Expert Systems with Applications, 2022 - Elsevier
Abstract The aim of Vehicular Ad Hoc Networks (VANETs) is to provide drivers and
passengers with various applications and services for comfortable transportation by …

IDERES: Intrusion detection and response system using machine learning and attack graphs

JR Rose, M Swann, KP Grammatikakis, I Koufos… - Journal of Systems …, 2022 - Elsevier
The rapid increase in the use of IoT devices brings many benefits to the digital society,
ranging from improved efficiency to higher productivity. However, the limited resources and …

Machine Learning in Metaverse Security: Current Solutions and Future Challenges

Y Otoum, N Gottimukkala, N Kumar, A Nayak - ACM Computing Surveys, 2024 - dl.acm.org
The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a
virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self …

Intrusion Detection System in Software-Defined Networks Using Machine Learning and Deep Learning Techniques--A Comprehensive Survey

MR Ahmed, S Shatabda, AKMM Islam, MTI Robin - Authorea Preprints, 2023 - techrxiv.org
At present, the Internet is facing numerous attacks of different kinds that put its data at risk.
The safety of information within the network is, therefore, a significant concern. To prevent …

SD-IIDS: intelligent intrusion detection system for software-defined networks

NS Shaji, R Muthalagu, PM Pawar - Multimedia Tools and Applications, 2024 - Springer
Abstract Software-Defined Networking (SDN) is susceptible to security threats despite all the
network programmability and flexibility offered, and hence SDN must be safeguarded. This …

Intrusion detection using network traffic profiling and machine learning for IoT

JR Rose, M Swann, G Bendiab… - 2021 IEEE 7th …, 2021 - ieeexplore.ieee.org
The rapid increase in the use of IoT devices brings many benefits to the digital society,
ranging from improved efficiency to higher productivity. However, the limited resources and …