scholarly journals Deep learning based network traffic matrix prediction

2021 ◽  
Vol 2 ◽  
pp. 46-56
Author(s):  
Dalal Aloraifan ◽  
Imtiaz Ahmad ◽  
Ebrahim Alrashed
Keyword(s):  
Deep Learning ◽  
Network Traffic ◽  
Traffic Matrix

scholarly journals Real-Time Detection of Dictionary DGA Network Traffic Using Deep Learning

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Kate Highnam ◽  
Domenic Puzio ◽  
Song Luo ◽  
Nicholas R. Jennings
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
Network Traffic ◽  
Short Term Memory ◽  
Domain Names ◽  
Control Networks ◽  
Detection Techniques ◽  
Lstm Network ◽  
And Control

AbstractBotnets and malware continue to avoid detection by static rule engines when using domain generation algorithms (DGAs) for callouts to unique, dynamically generated web addresses. Common DGA detection techniques fail to reliably detect DGA variants that combine random dictionary words to create domain names that closely mirror legitimate domains. To combat this, we created a novel hybrid neural network, Bilbo the “bagging” model, that analyses domains and scores the likelihood they are generated by such algorithms and therefore are potentially malicious. Bilbo is the first parallel usage of a convolutional neural network (CNN) and a long short-term memory (LSTM) network for DGA detection. Our unique architecture is found to be the most consistent in performance in terms of AUC, $$F_1$$ F 1 score, and accuracy when generalising across different dictionary DGA classification tasks compared to current state-of-the-art deep learning architectures. We validate using reverse-engineered dictionary DGA domains and detail our real-time implementation strategy for scoring real-world network logs within a large enterprise. In 4 h of actual network traffic, the model discovered at least five potential command-and-control networks that commercial vendor tools did not flag.

A Novel Non-Supervised Deep-Learning-Based Network Traffic Control Method for Software Defined Wireless Networks

2018 ◽  
Vol 25 (4) ◽  
pp. 74-81 ◽  
Author(s):  
Bomin Mao ◽  
Fengxiao Tang ◽  
Zubair Md. Fadlullah ◽  
Nei Kato ◽  
Osamu Akashi ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Deep Learning ◽  
Network Traffic ◽  
Traffic Control ◽  
Control Method

scholarly journals Datanet: Deep Learning Based Encrypted Network Traffic Classification in SDN Home Gateway

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 55380-55391 ◽  
Author(s):  
Pan Wang ◽  
Feng Ye ◽  
Xuejiao Chen ◽  
Yi Qian
Keyword(s):  
Deep Learning ◽  
Network Traffic ◽  
Traffic Classification ◽  
Home Gateway ◽  
Network Traffic Classification

Traffic Matrix Prediction Based on Deep Learning for Dynamic Traffic Engineering

2019 ◽  
Author(s):  
Zhifeng Liu ◽  
Zhiliang Wang ◽  
Xia Yin ◽  
Xingang Shi ◽  
Yingya Guo ◽  
...  
Keyword(s):  
Deep Learning ◽  
Traffic Engineering ◽  
Dynamic Traffic ◽  
Traffic Matrix

A deep learning method based on an attention mechanism for wireless network traffic prediction

2020 ◽  
Vol 107 ◽  
pp. 102258 ◽  
Author(s):  
Ming Li ◽  
Yuewen Wang ◽  
Zhaowen Wang ◽  
Huiying Zheng
Keyword(s):  
Deep Learning ◽  
Wireless Network ◽  
Network Traffic ◽  
Attention Mechanism ◽  
Traffic Prediction ◽  
Learning Method
Sign in / Sign up

Export Citation Format

Share Document