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 …

[HTML][HTML] A comprehensive survey on knowledge-defined networking

PADSN Wijesekara, S Gunawardena - Telecom, 2023 - mdpi.com
Traditional networking is hardware-based, having the control plane coupled with the data
plane. Software-Defined Networking (SDN), which has a logically centralized control plane …

A flexible SDN-based framework for slow-rate DDoS attack mitigation by using deep reinforcement learning

NM Yungaicela-Naula, C Vargas-Rosales… - Journal of network and …, 2022 - Elsevier
Abstract Distributed Denial-of-Service (DDoS) attacks are difficult to mitigate with existing
defense tools. Fortunately, it has been demonstrated that Software-Defined Networking …

Towards security automation in software defined networks

NM Yungaicela-Naula, C Vargas-Rosales… - Computer …, 2022 - Elsevier
Abstract Software-Defined Networking (SDN) is a modern paradigm that provides a platform
for implementing reliable, centrally managed, and automated security solutions for …

A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions

M Ozkan-Ozay, E Akin, Ö Aslan, S Kosunalp… - IEEE …, 2024 - ieeexplore.ieee.org
Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence
methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement …

DRL-QOR: Deep reinforcement learning-based QoS/QoE-aware adaptive online orchestration in NFV-enabled networks

J Chen, J Chen, H Zhang - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
Faced with fluctuating network traffic and unknown underlying network traffic dynamics,
developing an effective orchestration model with low network cost is still a critical issue in …

Chronos: Ddos attack detection using time-based autoencoder

MA Salahuddin, V Pourahmadi… - … on Network and …, 2021 - ieeexplore.ieee.org
Cognitive network management is becoming quintessential to realize autonomic networking.
However, the wide spread adoption of the Internet of Things (IoT) devices, increases the risk …

DeepAir: Deep reinforcement learning for adaptive intrusion response in software-defined networks

TV Phan, T Bauschert - IEEE Transactions on Network and …, 2022 - ieeexplore.ieee.org
In this paper, we propose an adaptive intrusion response solution based on deep
reinforcement learning, namely DeepAir, to effectively defend against cyber-attacks in …

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 …

[HTML][HTML] Multi-agent reinforcement learning framework in sdn-iot for transient load detection and prevention

DK Dake, JD Gadze, GS Klogo, H Nunoo-Mensah - Technologies, 2021 - mdpi.com
The fast emergence of IoT devices and its accompanying big and complex data has
necessitated a shift from the traditional networking architecture to software-defined networks …