Results 151 to 160 of about 21,088 (211)

A Mining Policy based Malicious Encrypted Traffic Detection Scheme

Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition, 2020
Malicious encrypted traffic poses a great threat to cyber space owing to its ability to bypass traditional traffic detection schemes. Malicious encrypted traffic detection is a challenging task and has attracted researchers' attention nowadays. Specifically, the detection task is subject to difficult feature mining and unsatisfactory results. Therefore,
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Encrypted Malicious Traffic Detection Based on Graph Convolutional Network and Temporal Dissection

International Conference on Computer Supported Cooperative Work in Design
With the rapid development of the Internet, network security issues are receiving increasing attention and various network attack methods are emerging, among which encrypted malicious traffic, as a common attack method, has become a major challenge in ...
Yuchen Liu, Shanshan Wang, Jin Au-Yeung, Zhenxiang Chen   +3 more
semanticscholar   +1 more source

AGAE: Unsupervised Anomaly Detection for Encrypted Malicious Traffic

APWeb/WAIM
Hao Wang, Ye Wang, Zhaoquan Gu, Yan Jia
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TB-Graph: Enhancing Encrypted Malicious Traffic Classification through Relational Graph Attention Networks

Computers, Materials & Continua
The proliferation of internet traffic encryption has become a double-edged sword. While it significantly enhances user privacy, it also inadvertently shields cyber-attacks from detection, presenting a formidable challenge to cybersecurity.
Ming Liu, Qichao Yang, Wenqing Wang, Shengli Liu   +3 more
semanticscholar   +1 more source

CoMDet: A Contrastive Multimodal Pre-Training Approach to Encrypted Malicious Traffic Detection

Annual International Computer Software and Applications Conference
Encrypted malicious traffic detection aims at iden-tifying malicious activities without decrypting network traffic, which is essential for cybersecurity.
Jiakun Sun, Xiaotian Zhang, Yabo Wang, Shuyuan Jin   +3 more
semanticscholar   +1 more source

Few-shot Encrypted Malicious Traffic Classification via Hierarchical Semantics and Adaptive Prototype Learning

International Conference on Trust, Security and Privacy in Computing and Communications
While encrypted traffic improves security, it is also used by attackers to hide the transmission content to evade detection. Currently, traffic side-channel features combined with Deep Learning (DL) are widely used for malicious traffic classification ...
Yuan Zhao, Chunhe Xia, Tianbo Wang, Mengyao Liu, Yang Li   +4 more
semanticscholar   +1 more source

Quantum deep learning for encrypted malicious traffic detection a hybrid approach for secure network analysis

Proceedings of Applied Data Science & Artificial Intelligence Symposium 2025
Cybersecurity threats have become more advanced, making encrypted network traffic essential for security while also challenging to monitor. Transport Layer Security (TLS) is widely used to protect online communications by ensuring data integrity and ...
N. Hariharan, P. Guhanathan
semanticscholar   +1 more source

An Encrypted Malicious Traffic Detection System Based on Neural Network

2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2019
In recent years, with the widespread use of encrypted traffic communication technology, network traffic encryption has been gradually becoming a standard of communication. This phenomenon has a great impact on traditional traffic detection methods, especially on anomaly detection methods, which are highly dependent on the type of network protocol types
Tangda Yu, FuTai Zou, Linsen Li, Ping Yi
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Encrypted Malicious Traffic Detection in Power Systems Based on Graph Convolutional Networks

International Conference on Information Systems and Computer Aided Education
With the continuous expansion of the Internet scale, Internet applications have penetrated into all areas of the society, and the network attack events have seriously threatened the national security, social stability and the security of personal ...
Xin Xu, Gang Qu, Yi Wu
semanticscholar   +1 more source

MFD: Multidimensional Feature Fusion and Masked Autoencoder for Encrypted Malicious Traffic Detection

IEEE International Conference on Systems, Man and Cybernetics
The classification of encrypted network traffic (ENTC) is vital for ensuring network security, effective administration, and maintaining service quality. To accurately detect malicious encrypted traffic in communications and overcome the challenges posed
Chenhao Liu, Xinwang Ding, Lina Wang, Zhi Pang, Chenye Yang, Bofei Jia, Rongwei Yu   +6 more
semanticscholar   +1 more source