[HTML][HTML] A standalone photovoltaic/battery energy-powered water quality monitoring system based on narrowband internet of things for aquaculture: Design and …

C Jamroen, N Yonsiri, T Odthon, N Wisitthiwong… - Smart Agricultural …, 2023 - Elsevier
This study presents a standalone photovoltaic (PV)/battery energy storage (BES)-powered
water quality monitoring system based on the narrowband internet of things (NB-IoT) for …

[HTML][HTML] Network traffic classification for data fusion: A survey

J Zhao, X Jing, Z Yan, W Pedrycz - Information Fusion, 2021 - Elsevier
Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …

Procedures, criteria, and machine learning techniques for network traffic classification: a survey

MS Sheikh, Y Peng - IEEE Access, 2022 - ieeexplore.ieee.org
Traffic classification is considered an important research area due to the increasing demand
in network users. It not only effectively improve the network service identifications and …

Is encrypted clienthello a challenge for traffic classification?

D Shamsimukhametov, A Kurapov… - IEEE …, 2022 - ieeexplore.ieee.org
Although the widely-used Transport Layer Security (TLS) protocol hides application data, an
unencrypted part of the TLS handshake, specifically the server name indication (SNI), is a …

[PDF][PDF] A comparative review of malware analysis and detection in HTTPs traffic

AP Singh, M Singh - Int. J. Com. Dig. Sys, 2021 - academia.edu
HTTPs is essentially an integration of the Hypertext Transfer Protocol with either TLS or SSL.
The responsibility of SSL/TLS in HTTPs is to encrypt the content of HTTP. Without …

A review on TLS encryption malware detection: TLS features, machine learning usage, and future directions

K Keshkeh, A Jantan, K Alieyan, UM Gana - Advances in Cyber Security …, 2021 - Springer
With the growth of internet encryption to protect users' privacy, malware has evolved to
employ encryption protocols such as TLS/SSL to obfuscate the contents of malicious …

Android malware identification based on traffic analysis

R Chen, Y Li, W Fang - … conference on artificial intelligence and security, 2019 - Springer
As numerous new techniques for Android malware attacks have growingly emerged and
evolved, Android malware identification is extremely crucial to prevent mobile applications …

A communication-channel-based method for detecting deeply camouflaged malicious traffic

Y Fang, K Li, R Zheng, S Liao, Y Wang - Computer Networks, 2021 - Elsevier
We present a novel method for detecting malicious TLS traffic based on communication
channels that can detect deeply camouflaged malicious traffic. Moreover, we designed and …

An empirical comparison of supervised algorithms for ransomware identification on network traffic

C Manzano, C Meneses, P Leger - 2020 39th International …, 2020 - ieeexplore.ieee.org
Android mobile systems are currently the main target of malware attacks. In this sense,
machine learning is a suitable approach to analyze network traffic, and it generally achieves …

Two-layer detection framework with a high accuracy and efficiency for a malware family over the TLS protocol

R Zheng, J Liu, L Liu, S Liao, K Li, J Wei, L Li, Z Tian - PloS one, 2020 - journals.plos.org
The transport layer security (TLS) protocol is widely adopted by apps as well as malware.
With the geometric growth of TLS traffic, accurate and efficient detection of malicious TLS …