Machine learning-powered encrypted network traffic analysis: A comprehensive survey

M Shen, K Ye, X Liu, L Zhu, J Kang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

Security in SDN: A comprehensive survey

JCC Chica, JC Imbachi, JFB Vega - Journal of Network and Computer …, 2020 - Elsevier
Abstract Software Defined Networking (SDN) is a revolutionary paradigm that is maturing
along with other network technologies in the next-gen trend. The separation of control and …

Anomaly-based intrusion detection system for IoT networks through deep learning model

T Saba, A Rehman, T Sadad, H Kolivand… - Computers and Electrical …, 2022 - Elsevier
Abstract The Internet of Things (IoT) idea has been developed to enhance people's lives by
delivering a diverse range of smart interconnected devices and applications in several …

Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system

V Ravi, R Chaganti, M Alazab - Computers and Electrical Engineering, 2022 - Elsevier
This work proposes an end-to-end model for network attack detection and network attack
classification using deep learning-based recurrent models. The proposed model extracts the …

InSDN: A novel SDN intrusion dataset

MS Elsayed, NA Le-Khac, AD Jurcut - IEEE access, 2020 - ieeexplore.ieee.org
Software-Defined Network (SDN) has been developed to reduce network complexity
through control and manage the whole network from a centralized location. Today, SDN is …

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 …

Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation

BA Tama, S Lim - Computer Science Review, 2021 - Elsevier
Intrusion detection systems (IDSs) are intrinsically linked to a comprehensive solution of
cyberattacks prevention instruments. To achieve a higher detection rate, the ability to design …

SDN‐based intrusion detection system for IoT using deep learning classifier (IDSIoT‐SDL)

A Wani, R Khaliq - CAAI Transactions on Intelligence …, 2021 - Wiley Online Library
The participation of ordinary devices in networking has created a world of connected
devices rapidly. The Internet of Things (IoT) includes heterogeneous devices from every …

Machine learning based intrusion detection system for software defined networks

A Abubakar, B Pranggono - 2017 seventh international …, 2017 - ieeexplore.ieee.org
Software-Defined Networks (SDN) is an emerging area that promises to change the way we
design, build, and operate network architecture. It tends to shift from traditional network …

An SDN-based intrusion detection system using SVM with selective logging for IP traceback

P Hadem, DK Saikia, S Moulik - Computer Networks, 2021 - Elsevier
In this paper we introduce a Software Defined Networking (SDN) based Intrusion Detection
System (IDS) using the Support Vector Machines (SVM) along with Selective Logging for IP …