Results 251 to 260 of about 3,911,620 (341)

A Novel Multimodal Deep Learning Framework for Encrypted Traffic Classification

IEEE/ACM Transactions on Networking, 2023
Traffic classification is essential for cybersecurity maintenance and network management, and has been widely used in QoS (Quality of Service) guarantees, intrusion detection, and other tasks.
Peng Lin, Kejiang Ye, Yishen Hu, Yanying Lin, Chengjie Xu   +4 more
semanticscholar   +1 more source

Flow-Based Encrypted Network Traffic Classification With Graph Neural Networks

IEEE Transactions on Network and Service Management, 2023
Classifying encrypted traffic from emerging applications is important but challenging as many conventional traffic classification approaches are ineffective, thus calling for novel methods for identifying encrypted network flows.
Ting-Li Huoh, Yan Luo, Peilong Li, Tong Zhang   +3 more
semanticscholar   +1 more source

Rosetta: Enabling Robust TLS Encrypted Traffic Classification in Diverse Network Environments with TCP-Aware Traffic Augmentation

USENIX Security Symposium, 2023
As the majority of Internet traffic is encrypted by the Transport Layer Security (TLS) protocol, recent advances leverage Deep Learning (DL) models to conduct encrypted traffic classification.
Renjie Xie, Yixiao Wang, Jiahao Cao, Enhuan Dong, Mingwei Xu, Kun Sun, Qi Li, Licheng Shen, Menghao Zhang   +8 more
semanticscholar   +1 more source

Flow-MAE: Leveraging Masked AutoEncoder for Accurate, Efficient and Robust Malicious Traffic Classification

International Symposium on Recent Advances in Intrusion Detection, 2023
Malicious traffic classification is crucial for Intrusion Detection Systems (IDS). However, traditional Machine Learning approaches necessitate expert knowledge and a significant amount of well-labeled data.
Zijun Hang, Yuliang Lu, Yongjie Wang, Yi Xie   +3 more
semanticscholar   +1 more source

Deep learning for encrypted traffic classification in the face of data drift: An empirical study

Comput. Networks, 2023
Deep learning models have shown to achieve high performance in encrypted traffic classification. However, when it comes to production use, multiple factors challenge the performance of these models.
Navid Malekghaini, Elham Akbari, M. A. Salahuddin, Noura Limam, R. Boutaba, B. Mathieu, S. Moteau, Stéphane Tuffin   +7 more
semanticscholar   +1 more source

R1DIT: Privacy-Preserving Malware Traffic Classification With Attention-Based Neural Networks

IEEE Transactions on Network and Service Management, 2023
With the advances in deep learning techniques and the increase in the volume of network traffic data, deep neural networks trained directly with the raw traffic data have become more popular and successful for malware traffic classification without ...
Onur Barut, Yan Luo, Peilong Li, Tong Zhang   +3 more
semanticscholar   +1 more source

IoT Network Traffic Classification Using Machine Learning Algorithms: An Experimental Analysis

The International Conference on scientific innovations in Science, Technology, and Management, 2023
In this project, classification of IoT network traffic using random forest classifier is proposed. More-dataset is utilized to separate the IoT traffic classification. Data preprocessing is the concept of changing the raw data into a clean data set.
Evelyn Lisa E, Ajeesha T. L.
semanticscholar   +1 more source

A Network Traffic Classification Method Based on Dual-Mode Feature Extraction and Hybrid Neural Networks

IEEE Transactions on Network and Service Management, 2023
Network traffic classification is a key foundation of traffic management and network security. With the development of traffic encryption technologies and more attention given to user privacy, traditional rule-based and payload-based traffic ...
Yang Yang, Yu Yan, Zhipeng Gao, Lanlan Rui, Rui Lyu, Bowen Gao, Peng Yu   +6 more
semanticscholar   +1 more source

Encrypted Traffic Classification Based on Traffic Reconstruction

2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD), 2021
Network traffic classification is to classify network traffic into related traffic types, which plays a significant role in network management and network security. It can guarantee the quality of service of the network, and guarantee network security by intercepting malware traffic.
Qianli Ma, Wei Huang, Yanliang Jin, Jianhua Mao   +3 more
openaire   +1 more source