Results 31 to 40 of about 21,088 (211)

Feature analysis of encrypted malicious traffic

Expert Systems with Applications, 2019
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation or communication. Antivirus software and firewalls typically will not have access to encryption keys, and therefore direct detection of malicious encrypted data is unlikely to succeed. However, previous work has shown
Shekhawat, Anish Singh, Di Troia, Fabio, Stamp, Mark   +2 more
openaire   +2 more sources

Study on SSL/TLS Encrypted Malicious Traffic Detection Algorithm Based on Graph Neural Networks [PDF]

Jisuanji kexue
In order to achieve precise detection of SSL/TLS encrypted malicious traffic,a graph neural network-based model for malicious encrypted traffic detection is proposed,to address the issue of excessive reliance on expert experience in traditional machine ...
TANG Ying, WANG Baohui
doaj   +1 more source

A VPN-Encrypted Traffic Identification Method Based on Ensemble Learning

Applied Sciences, 2022
One of the foundational and key means of optimizing network service in the field of network security is traffic identification. Various data transmission encryption technologies have been widely employed in recent years.
Jie Cao, Xing-Liang Yuan, Ying Cui, Jia-Cheng Fan, Chin-Ling Chen   +4 more
doaj   +1 more source

Study on privacy preserving encrypted traffic detection

网络与信息安全学报, 2021
Existing encrypted traffic detection technologies lack privacy protection for data and models, which will violate the privacy preserving regulations and increase the security risk of privacy leakage.A privacy-preserving encrypted traffic detection system
Xinyu ZHANG, Bingsheng ZHANG, Quanrun MENG, Kui REN   +3 more
doaj   +3 more sources

Anomaly Detection Using XGBoost Ensemble of Deep Neural Network Models

Cybernetics and Information Technologies, 2021
Intrusion Detection Systems (IDSs) utilise deep learning techniques to identify intrusions with maximum accuracy and reduce false alarm rates. The feature extraction is also automated in these techniques.
Ikram Sumaiya Thaseen, Cherukuri Aswani Kumar, Poorva Babu, Ushasree Pamidi Sai, Zhang Yishuo, Liu Xiao, Li Gang   +6 more
doaj   +1 more source

Review of Key Technologies of Incremental Intrusion Detection for Network Encrypted Traffic [PDF]

Jisuanji gongcheng
As cyber threats continue to intensify, the concealment of encrypted traffic attacks and the suddenness of zero-day exploits have significantly reduced the detection efficiency of traditional intrusion detection systems.
CHEN Liangchen, FU Deyin, LIU Baoxu, GAO Shu, ZHANG Xuyao
doaj   +1 more source

Identification of encrypted and malicious network traffic based on one-dimensional convolutional neural network

Journal of Cloud Computing: Advances, Systems and Applications, 2023
The rapid advancement of the Internet has brought a exponential growth in network traffic. At present, devices deployed at edge nodes process huge amount of data, extract key features of network traffic and then forward them to the cloud server/data ...
Yan Zhou, Huiling Shi, Yanling Zhao, Wei Ding, Jing Han, Hongyang Sun, Xianheng Zhang, Chang Tang, Wei Zhang   +8 more
doaj   +1 more source

DEV-ETA: An Interpretable Detection Framework for Encrypted Malicious Traffic

The Computer Journal, 2022
Abstract Traffic encrypted technology enables Internet users to protect their data secrecy, but it also brings a challenge to malicious package detection. To tackle this issue, researchers have investigated into encrypted traffic analysis (ETA) in recent years.
Luming Yang, Shaojing Fu, Yongjun Wang, Kaitai Liang, Fan Mo, Bo Liu   +5 more
openaire   +1 more source

Spatial-Temporal Feature with Dual-Attention Mechanism for Encrypted Malicious Traffic Detection

Security and Communication Networks, 2023
While encryption ensures the confidentiality and integrity of user data, more and more attackers try to hide attack behaviours through encryption, which brings new challenges to malicious traffic identification.
Jianyi Liu, Lanting Wang, Wei Hu, Yating Gao, Yaofu Cao, Bingjie Lin, Ru Zhang   +6 more
semanticscholar   +1 more source

Adversarial Malicious Encrypted Traffic Detection Based on Refined Session Analysis

Symmetry, 2022
The detection of malicious encrypted traffic is an important part of modern network security research. The producers of the current malware do not pay attention to the fact that malicious encrypted traffic can also be detected; they do not construct further adversarial malicious encrypted traffic to deceive existing malicious encrypted traffic ...
Minghui Li, Zhendong Wu, Keming Chen, Wenhai Wang   +3 more
openaire   +1 more source