Intelligent techniques for detecting network attacks: review and research directions

M Aljabri, SS Aljameel, RMA Mohammad, SH Almotiri… - Sensors, 2021 - mdpi.com
The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …

Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial–temporal features extraction

G D'Angelo, F Palmieri - Journal of Network and Computer Applications, 2021 - Elsevier
The right choice of features to be extracted from individual or aggregated observations is an
extremely critical factor for the success of modern network traffic classification approaches …

An autoML network traffic analyzer for cyber threat detection

A Papanikolaou, A Alevizopoulos, C Ilioudis… - International Journal of …, 2023 - Springer
Timely detection and effective treatment of cyber-attacks for protecting personal and
sensitive data from unauthorized disclosure constitute a core demand of citizens and a legal …

SDN-enabled FiWi-IoT smart environment network traffic classification using supervised ML models

E Ganesan, IS Hwang, AT Liem, MS Ab-Rahman - Photonics, 2021 - mdpi.com
Due to the rapid growth of the Internet of Things (IoT), applications such as the Augmented
Reality (AR)/Virtual Reality (VR), higher resolution media stream, automatic vehicle driving …

Enhanced Intrusion Detection in In-Vehicle Networks using Advanced Feature Fusion and Stacking-Enriched Learning

A Altalbe - IEEE Access, 2023 - ieeexplore.ieee.org
Modern vehicles rely heavily on interconnected electronic control units (ECUs) through in-
vehicle networks to perform crucial functions such as braking and monitoring engine RPMs …

A hybrid online classifier system for internet traffic based on statistical machine learning approach and flow port number

HAH Ibrahim, ORAL Zuobi, AM Abaker, MB Alzghoul - Applied Sciences, 2021 - mdpi.com
Internet traffic classification is a beneficial technique in the direction of intrusion detection
and network monitoring. After several years of searching, there are still many open problems …

Improved Video QoE in Wireless Networks Using Deep Reinforcement Learning

HD Moura, JM Oliveira, D Soares… - … on Network and …, 2023 - ieeexplore.ieee.org
Millions of videos are watched per minute on the Internet. Due to real-time performance
demands, such as high-quality video streaming, network administrators face new challenges …

Detecting malicious domains using the splunk machine learning toolkit

M Cersosimo, A Lara - NOMS 2022-2022 IEEE/IFIP Network …, 2022 - ieeexplore.ieee.org
Malicious domains are often hidden amongst benign DNS requests. Given that DNS traffic is
generally permitted, blocking malicious requests is a challenge for most network defenses …

A blockchained automl network traffic analyzer to industrial cyber defense and protection

A Papanikolaou, A Alevizopoulos, C Ilioudis… - Electronics, 2023 - mdpi.com
Network traffic analysis can raise privacy concerns due to its ability to reveal sensitive
information about individuals and organizations. This paper proposes a privacy-preserving …

[PDF][PDF] ODTC: An online darknet traffic classification model based on multimodal self-attention chaotic mapping features

J Zhai, H Sun, C Xu, W Sun - Electronic Research Archive, 2023 - aimspress.com
Darknet traffic classification is significantly important to network management and security.
To achieve fast and accurate classification performance, this paper proposes an online …