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Seeing Traffic Paths: Encrypted Traffic Classification With Path Signature Features
IEEE Transactions on Information Forensics and Security, 2022Although many network traffic protection methods have been developed to protect user privacy, encrypted traffic can still reveal sensitive user information with sophisticated analysis.
Shiqian Xu +4 more
semanticscholar +1 more source
IEEE Internet of Things Journal, 2023
Network traffic classification is the foundation for many network security and network management applications. Recently, to preserve the privacy of the data which are generated in the mobile ends, federated learning (FL)-based classification methods are
Yingya Guo, Dan Wang
semanticscholar +1 more source
Network traffic classification is the foundation for many network security and network management applications. Recently, to preserve the privacy of the data which are generated in the mobile ends, federated learning (FL)-based classification methods are
Yingya Guo, Dan Wang
semanticscholar +1 more source
Encrypted traffic classification: the QUIC case
Traffic Monitoring and Analysis, 2023The QUIC protocol is a new reliable and secure transport protocol that is an alternative to TLS over TCP. However, compared to TLS, QUIC obfuscates the connection hand-shake and the server name indication domain, making a simple inspection more ...
Jan Luxemburk, Karel Hynek, T. Čejka
semanticscholar +1 more source
Encrypted TLS Traffic Classification on Cloud Platforms
IEEE/ACM Transactions on Networking, 2023Nowadays, encryption technology has been widely used to protect user privacy. With the explosive growth of mobile Internet, encrypted TLS traffic rises sharply and occupies a great share of current Internet traffic.
Xiao-chun Yun +4 more
semanticscholar +1 more source
IoT Network Traffic Classification Using Machine Learning Algorithms: An Experimental Analysis
IEEE Internet of Things Journal, 2022Internet of Things (IoT) refers to a wide variety of embedded devices connected to the Internet, enabling them to transmit and share information in smart environments with each other.
Rakesh Kumar +3 more
semanticscholar +1 more source
Accurate Traffic Classification
2007 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, 2007The analysis of network traffic can provide important information for network operators and administrators. One of the main purposes of traffic analysis is to identify the traffic mixture the network carries. A couple of different approaches have been proposed in the literature, but none of them performs well for all different application traffic types
Szabó, Géza +2 more
openaire +1 more source
IEEE Transactions on Network and Service Management, 2021
Identifying the type of a network flow or a specific application has many advantages, such as, traffic engineering, or to detect and prevent application or application types that violate the organization’s security policy.
T. Shapira, Y. Shavitt
semanticscholar +1 more source
Identifying the type of a network flow or a specific application has many advantages, such as, traffic engineering, or to detect and prevent application or application types that violate the organization’s security policy.
T. Shapira, Y. Shavitt
semanticscholar +1 more source
DISTILLER: Encrypted traffic classification via multimodal multitask deep learning
Journal of Network and Computer Applications, 2021Traffic classification, i.e. the inference of applications and/or services from their network traffic, represents the workhorse for service management and the enabler for valuable profiling information.
Giuseppe Aceto +3 more
semanticscholar +1 more source
Journal of Network and Computer Applications, 2021
The right choice of features to be extracted from individual or aggregated observations is an extremely critical factor for the success of modern network traffic classification approaches based on machine learning. Such activity, usually in charge of the
Gianni D’Angelo, F. Palmieri
semanticscholar +1 more source
The right choice of features to be extracted from individual or aggregated observations is an extremely critical factor for the success of modern network traffic classification approaches based on machine learning. Such activity, usually in charge of the
Gianni D’Angelo, F. Palmieri
semanticscholar +1 more source
Multi class SVM algorithm with active learning for network traffic classification
Expert systems with applications, 2021With the current massive amount of traffic that is going through the internet, internet service providers (ISPs) and networking service providers (NSPs) are looking for various ways to accurately predict the application type of flow that is going through
Shi Dong
semanticscholar +1 more source