Machine learning-powered encrypted network traffic analysis: A comprehensive survey
Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …
and gleaning valuable information from network traffic. It can be applied in various fields …
CETAnalytics: Comprehensive effective traffic information analytics for encrypted traffic classification
Encrypted traffic classification is of great significance for advanced network services. Though
encryption methods seem unbroken in protecting users' privacy, existing studies have …
encryption methods seem unbroken in protecting users' privacy, existing studies have …
: A Deep Learning Based Network Encrypted Traffic Classification and Intrusion Detection Framework
Y Zeng, H Gu, W Wei, Y Guo - IEEE Access, 2019 - ieeexplore.ieee.org
With the rapid evolution of network traffic diversity, the understanding of network traffic has
become more pivotal and more formidable. Previously, traffic classification and intrusion …
become more pivotal and more formidable. Previously, traffic classification and intrusion …
An encrypted traffic classification method combining graph convolutional network and autoencoder
The increase in the source and size of encrypted network traffic brings significant challenges
for network traffic analysis. The challenging problem in the encrypted traffic classification …
for network traffic analysis. The challenging problem in the encrypted traffic classification …
Flow-based encrypted network traffic classification with graph neural networks
Classifying encrypted traffic from emerging applications is important but challenging as
many conventional traffic classification approaches are ineffective, thus calling for novel …
many conventional traffic classification approaches are ineffective, thus calling for novel …
Toward effective mobile encrypted traffic classification through deep learning
Traffic Classification (TC), consisting in how to infer applications generating network traffic, is
currently the enabler for valuable profiling information, other than being the workhorse for …
currently the enabler for valuable profiling information, other than being the workhorse for …
Machine learning for encrypted malicious traffic detection: Approaches, datasets and comparative study
As people's demand for personal privacy and data security becomes a priority, encrypted
traffic has become mainstream in the cyber world. However, traffic encryption is also …
traffic has become mainstream in the cyber world. However, traffic encryption is also …
A survey on encrypted network traffic analysis applications, techniques, and countermeasures
E Papadogiannaki, S Ioannidis - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The adoption of network traffic encryption is continually growing. Popular applications use
encryption protocols to secure communications and protect the privacy of users. In addition …
encryption protocols to secure communications and protect the privacy of users. In addition …
A survey of methods for encrypted traffic classification and analysis
With the widespread use of encrypted data transport, network traffic encryption is becoming
a standard nowadays. This presents a challenge for traffic measurement, especially for …
a standard nowadays. This presents a challenge for traffic measurement, especially for …
Optimizing feature selection for efficient encrypted traffic classification: A systematic approach
Traffic classification is a technology for classifying and identifying sensitive information from
cluttered traffic. With the increasing use of encryption and other evasion technologies …
cluttered traffic. With the increasing use of encryption and other evasion technologies …