Malicious traffic detection on sampled network flow data with novelty-detection-based models [PDF]
Scientific Reports, 2023 Cyber-attacks are a major problem for users, businesses, and institutions. Classical anomaly detection techniques can detect malicious traffic generated in a cyber-attack by analyzing individual network packets. However, routers that manage large traffic
Adrián Campazas-Vega +5 more
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Malicious traffic detection combined deep neural network with hierarchical attention mechanism [PDF]
Scientific Reports, 2021 Given the gradual intensification of the current network security situation, malicious attack traffic is flooding the entire network environment, and the current malicious traffic detection model is insufficient in detection efficiency and detection ...
Xiaoyang Liu, Jiamiao Liu
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Semi-Supervised Encrypted Malicious Traffic Detection Based on Multimodal Traffic Characteristics. [PDF]
Sensors (Basel)The exponential growth of encrypted network traffic poses significant challenges for detecting malicious activities online. The scale of emerging malicious traffic is significantly smaller than that of normal traffic, and the imbalanced data distribution poses challenges for detection. However, most existing methods rely on single-category features for
Liu M, Yang Q, Wang W, Liu S.
europepmc +4 more sources
A Framework for Malicious Traffic Detection in IoT Healthcare Environment. [PDF]
Sensors (Basel), 2021 The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT
Hussain F +7 more
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Malicious Traffic Detection Method for Power Monitoring Systems Based on Multi-Model Fusion Stacking Ensemble Learning [PDF]
SensorsWith the rapid development of the internet, the increasing amount of malicious traffic poses a significant challenge to the network security of critical infrastructures, including power monitoring systems.
Hao Zhang +6 more
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Encrypted malicious traffic detection based on neural network
Dianzi Jishu YingyongWith the widespread application of encrypted communications, traditional malicious traffic detection methods based on content analysis have gradually become ineffective.
Xia Longfei +5 more
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Obfuscated malicious traffic detection based on data enhancement
Frontiers in Computer ScienceAs the proportion of encrypted traffic increases, it becomes increasingly challenging for network attacks to be discovered. Although existing methods combine unencrypted statistical features, e.g., average packet length, with machine learning algorithms ...
Ke Ye +6 more
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Malicious DNS traffic detection based neural networks
Tongxin xuebaoTo solve the problems of low detection accuracy and speed caused by low efficiency in extracting traffic features using machine learning to detect malicious DNS traffic, a malicious DNS traffic detection method FDS-DL was proposed, which combines ...
SHAN Kangkang +3 more
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Encrypted Malicious Traffic Detection Based on Word2Vec [PDF]
Electronics, 2022 Network-based intrusion detections become more difficult as Internet traffic is mostly encrypted. This paper introduces a method to detect encrypted malicious traffic based on the Transport Layer Security handshake and payload features without waiting for the traffic session to finish while preserving privacy.
Andrey Ferriyan +3 more
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Encrypted Malicious Traffic Detection Based on Stacking and Multi-Feature Fusion [PDF]
Jisuanji gongcheng, 2023 Although encryption technology protects network communications，plenty malware uses encryption protocols to hide malicious behavior.For the existing Transport Layer Security（TLS） encrypted malicious traffic detection techniques based on machine learning，a
HUO Yuehua, ZHAO Faqi
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