Machine learning-powered encrypted network traffic analysis: A comprehensive survey

M Shen, K Ye, X Liu, L Zhu, J Kang… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
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 …

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 …

[HTML][HTML] Deep learning for network traffic monitoring and analysis (NTMA): A survey

M Abbasi, A Shahraki, A Taherkordi - Computer Communications, 2021 - Elsevier
Modern communication systems and networks, eg, Internet of Things (IoT) and cellular
networks, generate a massive and heterogeneous amount of traffic data. In such networks …

When machine learning meets privacy in 6G: A survey

Y Sun, J Liu, J Wang, Y Cao… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
The rapid-developing Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …

User-oriented virtual mobile network resource management for vehicle communications

H Lu, Y Zhang, Y Li, C Jiang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Currently, advanced communications and networks greatly enhance user experiences and
have a major impact on all aspects of people's lifestyles in terms of work, society, and the …

Boosting algorithms for network intrusion detection: A comparative evaluation of Real AdaBoost, Gentle AdaBoost and Modest AdaBoost

A Shahraki, M Abbasi, Ø Haugen - Engineering Applications of Artificial …, 2020 - Elsevier
Computer networks have been experienced ever-increasing growth since they play a critical
role in different aspects of human life. Regarding the vulnerabilities of computer networks …

Machine learning for encrypted malicious traffic detection: Approaches, datasets and comparative study

Z Wang, KW Fok, VLL Thing - Computers & Security, 2022 - Elsevier
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 …

[HTML][HTML] A comparative study on online machine learning techniques for network traffic streams analysis

A Shahraki, M Abbasi, A Taherkordi, AD Jurcut - Computer Networks, 2022 - Elsevier
Modern networks generate a massive amount of traffic data streams. Analyzing this data is
essential for various purposes, such as network resources management and cyber-security …

[PDF][PDF] Security enhancement by identifying attacks using machine learning for 5G network

H Keserwani, H Rastogi, AZ Kurniullah… - International Journal …, 2022 - researchgate.net
Need of security enhancement for 5G network has been increased in last decade. Data
transmitted over network need to be secure from external attacks. Thus there is need to …

Large-scale mobile app identification using deep learning

S Rezaei, B Kroencke, X Liu - IEEE Access, 2019 - ieeexplore.ieee.org
Many network services and tools (eg network monitors, malware-detection systems, routing
and billing policy enforcement modules in ISPs) depend on identifying the type of traffic that …