[HTML][HTML] Network traffic classification: Techniques, datasets, and challenges

A Azab, M Khasawneh, S Alrabaee, KKR Choo… - Digital Communications …, 2024 - Elsevier
In network traffic classification, it is important to understand the correlation between network
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …

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 …

A novel deep learning method for detection and classification of plant diseases

W Albattah, M Nawaz, A Javed, M Masood… - Complex & Intelligent …, 2022 - Springer
The agricultural production rate plays a pivotal role in the economic development of a
country. However, plant diseases are the most significant impediment to the production and …

MFF-GAN: An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion

H Zhang, Z Le, Z Shao, H Xu, J Ma - Information Fusion, 2021 - Elsevier
Multi-focus image fusion is an enhancement method to generate full-clear images, which
can address the depth-of-field limitation in imaging of optical lenses. Most existing methods …

XAI meets mobile traffic classification: Understanding and improving multimodal deep learning architectures

A Nascita, A Montieri, G Aceto… - … on Network and …, 2021 - ieeexplore.ieee.org
The increasing diffusion of mobile devices has dramatically changed the network traffic
landscape, with Traffic Classification (TC) surging into a fundamental role while facing new …

An efficient deep learning approach to automatic glaucoma detection using optic disc and optic cup localization

M Nawaz, T Nazir, A Javed, U Tariq, HS Yong… - Sensors, 2022 - mdpi.com
Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and
caused complete sightlessness at its progressed stage. Whereas timely glaucoma screening …

DISTILLER: Encrypted traffic classification via multimodal multitask deep learning

G Aceto, D Ciuonzo, A Montieri, A Pescapé - Journal of Network and …, 2021 - Elsevier
Traffic classification, ie the inference of applications and/or services from their network traffic,
represents the workhorse for service management and the enabler for valuable profiling …

Utilising deep learning techniques for effective zero-day attack detection

H Hindy, R Atkinson, C Tachtatzis, JN Colin, E Bayne… - Electronics, 2020 - mdpi.com
Machine Learning (ML) and Deep Learning (DL) have been used for building Intrusion
Detection Systems (IDS). The increase in both the number and sheer variety of new cyber …

Machine learning for encrypted malicious traffic detection: Approaches, datasets and comparative study

Z Wang, KW Fok, VLL Thing - Computers & Security, 2022 - Elsevier
As people's demand for personal privacy and data security becomes a priority, encrypted
traffic has become mainstream in the cyber world. However, traffic encryption is also …

TSCRNN: A novel classification scheme of encrypted traffic based on flow spatiotemporal features for efficient management of IIoT

K Lin, X Xu, H Gao - Computer Networks, 2021 - Elsevier
Abstract In the Industrial Internet of Things (IIoT) in the 5G era, the growth of smart devices
will generate a large amount of data traffic, bringing a huge challenge of network traffic …