[HTML][HTML] Robotics cyber security: Vulnerabilities, attacks, countermeasures, and recommendations

JPA Yaacoub, HN Noura, O Salman… - International Journal of …, 2022 - Springer
The recent digital revolution led robots to become integrated more than ever into different
domains such as agricultural, medical, industrial, military, police (law enforcement), and …

A review on machine learning–based approaches for Internet traffic classification

O Salman, IH Elhajj, A Kayssi, A Chehab - Annals of Telecommunications, 2020 - Springer
Traffic classification acquired the interest of the Internet community early on. Different
approaches have been proposed to classify Internet traffic to manage both security and …

SCNTA: Monitoring of network availability and activity for identification of anomalies using machine learning approaches

R Rawat, B Garg, K Pachlasiya, V Mahor… - International Journal of …, 2022 - igi-global.com
Real-time network inspection applications face a threat of vulnerability as high-speed
networks continue to expand. For companies and ISPs, real-time traffic classification is an …

A machine learning based framework for IoT device identification and abnormal traffic detection

O Salman, IH Elhajj, A Chehab… - Transactions on …, 2022 - Wiley Online Library
Network security is a key challenge for the deployment of Internet of Things (IoT). New
attacks have been developed to exploit the vulnerabilities of IoT devices. Moreover, IoT …

[HTML][HTML] Data transformation schemes for cnn-based network traffic analysis: A survey

J Krupski, W Graniszewski, M Iwanowski - Electronics, 2021 - mdpi.com
The enormous growth of services and data transmitted over the internet, the bloodstream of
modern civilization, has caused a remarkable increase in cyber attack threats. This fact has …

Procedures, criteria, and machine learning techniques for network traffic classification: a survey

MS Sheikh, Y Peng - IEEE Access, 2022 - ieeexplore.ieee.org
Traffic classification is considered an important research area due to the increasing demand
in network users. It not only effectively improve the network service identifications and …

GRAIN: Granular multi-label encrypted traffic classification using classifier chain

F Zaki, F Afifi, S Abd Razak, A Gani, NB Anuar - Computer Networks, 2022 - Elsevier
Granular traffic classification categorizes traffic into detailed classes like application names
and services. Application names represent parent applications, such as Facebook, while …

Data representation for CNN based internet traffic classification: a comparative study

O Salman, IH Elhajj, A Kayssi, A Chehab - Multimedia Tools and …, 2021 - Springer
It has been well established that the Internet of Things will bring an expansion in traffic
volume and types. This will bring new challenges in terms of Quality of Service (QoS) and …

CAPC: packet-based network service classifier with convolutional autoencoder

KC Chiu, CC Liu, LD Chou - Ieee Access, 2020 - ieeexplore.ieee.org
The Internet has been evolving from a traditional mechanism to a modern service-oriented
architecture, such as quality-of-service (QoS) policies, to meet users' various requirements …

[HTML][HTML] Method for multi-task learning fusion network traffic classification to address small sample labels

L Liu, Y Yu, Y Wu, Z Hui, J Lin, J Hu - Scientific Reports, 2024 - nature.com
In the context of the proliferated evolution of network service types and the expeditious
augmentation of network resource deployment, the requisition for copious labeled datasets …