Semi-Supervised Encrypted Malicious Traffic Detection Based on Multimodal Traffic Characteristics [PDF]
SensorsThe 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
Ming Liu +3 more
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Research on encrypted malicious traffic detection in power information interaction: application of the electricity multi-granularity flow representation learning approach [PDF]
Scientific ReportsWith the rapid digital transformation of power systems, encrypted communication technologies are increasingly adopted to enhance data privacy and security.
Zhifu Wu +5 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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Identification of Malicious Encrypted Traffic Through Feature Fusion
IEEE Access, 2023 The popularity of encrypted communication has grown due to increased security awareness and rapid internet development. End-to-end encryption can prevent data attacks but also poses new cybersecurity threats. Thus, identifying malicious encrypted traffic
Xianchun Zheng, Hui Li
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A novel encrypted traffic detection model based on detachable convolutional GCN-LSTM [PDF]
Scientific ReportsWith the widespread adoption of network encryption technologies, traditional detection methods increasingly struggle to identify malicious encrypted traffic due to their limited ability to capture structural and behavioral characteristics.
Xiaogang Yuan +3 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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Survey of encrypted malicious traffic detection based on deep learning
网络与信息安全学报, 2020 With the increasing awareness of network security, encrypted communication dominates and encrypted traffic grows rapidly. Traffic encryption, while protecting privacy, also masks illegal attempts and changes the form of threats.
ZHAI Mingfang, ZHANG Xingming, ZHAO Bo
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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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Encrypted Malicious Traffic Identification Based on Hierarchical Spatiotemporal Feature and Multi-Head Attention [PDF]
Jisuanji gongcheng, 2021 To implement the full encryption of Internet,the accurate detection of encrypted malicious traffic is required,but traditional detection methods rely heavily on expert experience and perform poorly in distiguishment of encrypted traffic feature is not ...
JIANG Tongtong, YIN Weixin, CAI Bing, ZHANG Kun
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Malicious Encryption Traffic Detection Based on NLP [PDF]
Security and Communication Networks, 2021 The development of Internet and network applications has brought the development of encrypted communication technology. But on this basis, malicious traffic also uses encryption to avoid traditional security protection and detection. Traditional security protection and detection methods cannot accurately detect encrypted malicious traffic.
Hao Yang +3 more
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