[HTML][HTML] Network traffic classification: Techniques, datasets, and challenges
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 …
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …
Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
S Shamshirband, M Fathi, AT Chronopoulos… - Journal of Information …, 2020 - Elsevier
With the increasing utilization of the Internet and its provided services, an increase in cyber-
attacks to exploit the information occurs. A technology to store and maintain user's …
attacks to exploit the information occurs. A technology to store and maintain user's …
XAI meets mobile traffic classification: Understanding and improving multimodal deep learning architectures
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 …
landscape, with Traffic Classification (TC) surging into a fundamental role while facing new …
Toward effective mobile encrypted traffic classification through deep learning
Traffic Classification (TC), consisting in how to infer applications generating network traffic, is
currently the enabler for valuable profiling information, other than being the workhorse for …
currently the enabler for valuable profiling information, other than being the workhorse for …
Characterization and prediction of mobile-app traffic using Markov modeling
Modeling network traffic is an endeavor actively carried on since early digital
communications, supporting a number of practical applications, that range from network …
communications, supporting a number of practical applications, that range from network …
[HTML][HTML] Fine-grained TLS services classification with reject option
J Luxemburk, T Čejka - Computer Networks, 2023 - Elsevier
The recent success and proliferation of machine learning and deep learning have provided
powerful tools, which are also utilized for encrypted traffic analysis, classification, and threat …
powerful tools, which are also utilized for encrypted traffic analysis, classification, and threat …
Contextual counters and multimodal Deep Learning for activity-level traffic classification of mobile communication apps during COVID-19 pandemic
The COVID-19 pandemic has reshaped Internet traffic due to the huge modifications
imposed to lifestyle of people resorting more and more to collaboration and communication …
imposed to lifestyle of people resorting more and more to collaboration and communication …
Packet-level prediction of mobile-app traffic using multitask deep learning
The prediction of network traffic characteristics helps in understanding this complex
phenomenon and enables a number of practical applications, ranging from network …
phenomenon and enables a number of practical applications, ranging from network …
A first look at class incremental learning in deep learning mobile traffic classification
The recent popularity growth of Deep Learning (DL) re-ignited the interest towards traffic
classification, with several studies demonstrating the accuracy of DL-based classifiers to …
classification, with several studies demonstrating the accuracy of DL-based classifiers to …
Extensible machine learning for encrypted network traffic application labeling via uncertainty quantification
S Jorgensen, J Holodnak, J Dempsey… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
With the increasing prevalence of encrypted network traffic, cybersecurity analysts have
been turning to machine learning (ML) techniques to elucidate the traffic on their networks …
been turning to machine learning (ML) techniques to elucidate the traffic on their networks …