Fs-net: A flow sequence network for encrypted traffic classification

C Liu, L He, G Xiong, Z Cao, Z Li - IEEE INFOCOM 2019-IEEE …, 2019 - ieeexplore.ieee.org
With more attention paid to user privacy and communication security, the volume of
encrypted traffic rises sharply, which brings a huge challenge to traditional rule-based traffic …

[Retracted] CLD‐Net: A Network Combining CNN and LSTM for Internet Encrypted Traffic Classification

X Hu, C Gu, F Wei - Security and Communication Networks, 2021 - Wiley Online Library
The development of the Internet has led to the complexity of network encrypted traffic.
Identifying the specific classes of network encryption traffic is an important part of …

Classify traffic rather than flow: Versatile multi-flow encrypted traffic classification with flow clustering

Z Chen, G Cheng, Z Wei, D Niu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Encrypted Traffic Classification (ETC) can provide necessary information support for network
management and security. The state-of-the-art ETC methods take a single flow as the unit …

STNN: A novel TLS/SSL encrypted traffic classification system based on stereo transform neural network

Y Zhang, S Zhao, J Zhang, X Ma… - 2019 IEEE 25th …, 2019 - ieeexplore.ieee.org
Nowadays, encrypted traffic classification has become a challenge for network monitoring
and cyberspace security. However, the existing methods cannot meet the requirements of …

M3F: A novel multi-session and multi-protocol based malware traffic fingerprinting

J Liu, Q Xiao, L Xin, Q Wang, Y Yao, Z Jiang - Computer Networks, 2023 - Elsevier
In recent years, cyber attacks have become increasingly frequent, which has had a
tremendous negative impact on public life and social order. Accurately and quickly finding …

App identification based on encrypted multi-smartphone sources traffic fingerprints

Q Ren, C Yang, J Ma - Computer Networks, 2021 - Elsevier
The smartphone app identification technology based on traffic fingerprints has begun to play
an important role in monitoring malware and assisting network management with the …

Instagram user behavior identification based on multidimensional features

H Wu, Q Wu, G Cheng, S Guo - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
The development of smartphones and social networks has brought great convenience to our
lives. Due to the increasing requirements of user privacy, user data are protected by …

SFIM: Identify user behavior based on stable features

H Wu, Q Wu, G Cheng, S Guo, X Hu, S Yan - Peer-to-Peer Networking and …, 2021 - Springer
The development of smartphones and social networks has brought great convenience to our
lives. Due to the increasing requirements of user privacy, user data are protected by …

Understanding Web Fingerprinting with a Protocol-Centric Approach

B Cebere, C Rossow - Proceedings of the 27th International Symposium …, 2024 - dl.acm.org
Recent breakthroughs in machine learning (ML) have unleashed several approaches to
fingerprinting web traffic based on traffic analysis. In particular, researchers report …

Packet length spectral analysis for IoT flow classification using ensemble learning

G Cirillo, R Passerone - IEEE Access, 2020 - ieeexplore.ieee.org
With the proliferation of ubiquitous and autonomous devices for sensing, control, monitoring
and conditioning, the Internet of Things (IoT) holds a great potential for the development of …