A survey on encrypted network traffic analysis applications, techniques, and countermeasures
E Papadogiannaki, S Ioannidis - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The adoption of network traffic encryption is continually growing. Popular applications use
encryption protocols to secure communications and protect the privacy of users. In addition …
encryption protocols to secure communications and protect the privacy of users. In addition …
Emerging DDoS attack detection and mitigation strategies in software-defined networks: Taxonomy, challenges and future directions
IA Valdovinos, JA Pérez-Díaz, KKR Choo… - Journal of Network and …, 2021 - Elsevier
Software-defined networking (SDN) is a network paradigm that decouples control and data
planes from network devices and places them into separate entities. In SDN, the controller is …
planes from network devices and places them into separate entities. In SDN, the controller is …
Performance evaluation of secured network traffic classification using a machine learning approach
AA Afuwape, Y Xu, JH Anajemba… - Computer Standards & …, 2021 - Elsevier
Network traffic classification is a significant and problematic aspect of network resource
management arising from an investigation of network developments, planning, and design …
management arising from an investigation of network developments, planning, and design …
Software-defined networking: Categories, analysis, and future directions
Software-defined networking (SDN) is an innovative network architecture that splits the
control and management planes from the data plane. It helps in simplifying network …
control and management planes from the data plane. It helps in simplifying network …
A novel method for improved network traffic prediction using enhanced deep reinforcement learning algorithm
Network data traffic is increasing with expanded networks for various applications, with text,
image, audio, and video for inevitable needs. Network traffic pattern identification and …
image, audio, and video for inevitable needs. Network traffic pattern identification and …
Predicting network flow characteristics using deep learning and real-world network traffic
We present a processing pipeline for flow-based traffic classification using a machine
learning component leveraging Deep Neural Networks (DNNs). The system is trained to …
learning component leveraging Deep Neural Networks (DNNs). The system is trained to …
Deep learning approach for SDN-enabled intrusion detection system in IoT networks
Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …
number of IoT-based attacks has been growing yearly. The existing solutions may not …
A survey of low-latency transmission strategies in software defined networking
B Yan, Q Liu, JL Shen, D Liang, B Zhao… - Computer Science …, 2021 - Elsevier
Abstract Software-defined networking (SDN), as a revolutionary networking paradigm,
provides a new solution for future network development and equipment manufacturing by …
provides a new solution for future network development and equipment manufacturing by …
Intelligent traffic management in next-generation networks
The recent development of smart devices has lead to an explosion in data generation and
heterogeneity. Hence, current networks should evolve to become more intelligent, efficient …
heterogeneity. Hence, current networks should evolve to become more intelligent, efficient …
Intrusion Detection System in Software-Defined Networks Using Machine Learning and Deep Learning Techniques--A Comprehensive Survey
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 …
The safety of information within the network is, therefore, a significant concern. To prevent …