ME-Box: A reliable method to detect malicious encrypted traffic

Author:

Xu BingfengORCID,He Gaofeng,Zhu HaitingORCID

Funder

Nanjing Forestry University

National Natural Science Foundation of China

Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality,Software

Reference49 articles.

1. More encrypted traffic than ever;Maddison,2018

2. IoT devices being increasingly used for DDoS attacks;Symantec Security Response,2016

3. Detect encrypted malware traffic and secure network;Cisco,2019

4. Multi-context TLS (mcTLS): Enabling secure in-network functionality in TLS;Naylor;ACM SIGCOMM Comput Commun Rev,2015

5. Building generic scalable middlebox services over encrypted protocols;Liu,2018

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2. Ensemble Learning for Encrypted Malware Detection and Classification;2023 International Conference on Information and Communication Technology for Development for Africa (ICT4DA);2023-10-26

3. Malicious encrypted network traffic flow detection using enhanced optimal deep feature selection with DLSTM;International Journal of Modeling, Simulation, and Scientific Computing;2023-07-19

4. Security is Readily to Interpret: Quantitative Feature Analysis for Botnet Encrypted Malicious Traffic;2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC);2023-06

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