Results 11 to 20 of about 1,873 (195)
IEEE Access, 2023 With the rapid advancement of the internet and online applications, traffic classification has become an increasingly significant topic in computer networks. Managing network resources, improving service quality, and enhancing cybersecurity are critical.
Mehdi Seydali +3 more
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Trustworthy deep learning for encrypted traffic classification
Soft Computing, 2022 Abstract Network traffic classification refers to the identification of collected network traffic data of various applications, which is widely used in research fields such as network resource allocation, traffic scheduling and intrusion detection systems.
Zheng Li +5 more
openaire +1 more source
Network traffic classification model based on attention mechanism and spatiotemporal features
EURASIP Journal on Information Security, 2023 Traffic classification is widely used in network security and network management. Early studies have mainly focused on mapping network traffic to different unencrypted applications, but little research has been done on network traffic classification of ...
Feifei Hu +5 more
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Encrypted traffic classification method based on convolutional neural network
网络与信息安全学报, 2022 Aiming at the problems of low accuracy, weak generality, and easy privacy violation of traditional encrypted network traffic classification methods, an encrypted traffic classification method based on convolutional neural network was proposed, which ...
Rongna XIE, Zhuhong MA, Zongyu LI, Ye TIAN
doaj +3 more sources
IET Communications, EarlyView., 2022 Abstract Mobile Ad‐hoc Network (MANET) is an ad hoc Wireless subset with a unique dynamic geometry of the system and movable nodes. The MANETs are auto‐organized networks that permit mobility without infrastructure. Specific protocols for MANET routing are provided with these attributes.
Shalini Goel +5 more
wiley +1 more source
CNN for User Activity Detection Using Encrypted In-App Mobile Data
Future Internet, 2022 In this study, a simple yet effective framework is proposed to characterize fine-grained in-app user activities performed on mobile applications using a convolutional neural network (CNN). The proposed framework uses a time window-based approach to split
Madushi H. Pathmaperuma +3 more
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Deep Learning-Based Efficient Analysis for Encrypted Traffic
Applied Sciences, 2023 To safeguard user privacy, critical Internet traffic is often transmitted using encryption. While encryption is crucial for protecting sensitive information, it poses challenges for traffic identification and poses hidden dangers to network security.
Xiaodan Yan
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Synonym‐based multi‐keyword ranked search with secure k‐NN in 6G network
IET Networks, EarlyView., 2022 Abstract Sixth Generation (6G) integrates the next generation communication systems such as maritime, terrestrial, and aerial to offer robust network and massive device connectivity with ultra‐low latency requirement. The cutting edge technologies such as artificial intelligence, quantum machine learning, and millimetre enable hyper‐connectivity to ...
Deebak Bakkiam David, Fadi Al‐Turjman
wiley +1 more source
ETRI Journal, 2020 Encrypted traffic classification plays a vital role in cybersecurity as network traffic encryption becomes prevalent. First, we briefly introduce three traffic encryption mechanisms: IPsec, SSL/TLS, and SRTP.
Kun Zhou +3 more
doaj +1 more source
Trigonometric words ranking model for spam message classification
IET Networks, EarlyView., 2022 Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source