An {Input-Agnostic} Hierarchical Deep Learning Framework for Traffic Fingerprinting
Deep learning has proven to be promising for traffic fingerprinting that explores features of
packet timing and sizes. Although well-known for automatic feature extraction, it is faced with …
packet timing and sizes. Although well-known for automatic feature extraction, it is faced with …
A real-time network traffic classifier for online applications using machine learning
AA Ahmed, G Agunsoye - Algorithms, 2021 - mdpi.com
The increasing ubiquity of network traffic and the new online applications' deployment has
increased traffic analysis complexity. Traditionally, network administrators rely on …
increased traffic analysis complexity. Traditionally, network administrators rely on …
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 …
Classifying and tracking enterprise assets via dual-grained network behavioral analysis
Enterprise networks continue to grow in scale and complexity, encompassing a wide range
of Internet-connected end-points including web servers/proxies, DNS/VPN/mail servers, and …
of Internet-connected end-points including web servers/proxies, DNS/VPN/mail servers, and …
Research on qos classification of network encrypted traffic behavior based on machine learning
In recent years, privacy awareness is concerned due to many Internet services have chosen
to use encrypted agreements. In order to improve the quality of service (QoS), the network …
to use encrypted agreements. In order to improve the quality of service (QoS), the network …
Improved harris combined with clustering algorithm for data traffic classification
Q Liu, M Li, N Cao, Z Zhang, G Yang - IEEE Access, 2022 - ieeexplore.ieee.org
Aiming at the problem that the data traffic in the intelligent wireless communication system
presents complex characteristics such as burstiness and self-similarity, which leads to the …
presents complex characteristics such as burstiness and self-similarity, which leads to the …
A novel graph convolutional networks model for an intelligent network traffic analysis and classification
Network security in the midst of evolving and complex cyber-attacks is a growing concern.
As the complexity of network architectures grows, so does the need for advanced methods in …
As the complexity of network architectures grows, so does the need for advanced methods in …
Fast online classification of network traffic using new feature-embedded hierarchical structure
Y Quan, Y Dong, Y Xiang, S Chen, Z Wang, J Jin - Computer Networks, 2023 - Elsevier
The fast online classification (FOC) of network traffic plays a critical role in the network
resource management and quality of service support. However, traditional network flow …
resource management and quality of service support. However, traditional network flow …
[HTML][HTML] Machine learning for sports betting: should model selection be based on accuracy or calibration?
C Walsh, A Joshi - Machine Learning with Applications, 2024 - Elsevier
Sports betting's recent federal legalisation in the USA coincides with the golden age of
machine learning. If bettors can leverage data to reliably predict the probability of an …
machine learning. If bettors can leverage data to reliably predict the probability of an …
User Classification and Traffic Steering in O-RAN
R Ntassah, GM Dell'area… - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
The O-RAN architectural framework enables the application of AI/ML techniques for traffic
steering and load balancing. Indeed, an effective steering technique is crucial to avoiding …
steering and load balancing. Indeed, an effective steering technique is crucial to avoiding …