Generating adversarial examples via enhancing latent spatial features of benign traffic and preserving malicious functions

被引：0

作者：

Zhang, Rongqian ^{[1
]}

Luo, Senlin ^{[1
]}

Pan, Limin ^{[1
]}

Hao, Jingwei ^{[1
]}

Zhang, Ji ^{[1
]}

机构：

[1] Information System and Security & Countermeasures Experimental Center, Beijing Institute of Technology, Beijing,100081, China

来源：

Neurocomputing | 2022年 / 490卷

关键词：

Adversarial attack - Classification models - Flow-based models - Generate adversarial example - Generation method - Intrusion Detection Systems - Neural network model - Original sample - Performance - Spatial features;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：413 / 430

共 5 条

[1] Generating adversarial examples via enhancing latent spatial features of benign traffic and preserving malicious functions
Zhang, Rongqian
Luo, Senlin
Pan, Limin
Hao, Jingwei
Zhang, Ji
NEUROCOMPUTING, 2022, 490 : 413 - 430
[2] Generating Semantic Adversarial Examples via Feature Manipulation in Latent Space
Wang, Shuo
Chen, Shangyu
Chen, Tianle
Nepal, Surya
Rudolph, Carsten
Grobler, Marthie
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (12) : 17070 - 17084
[3] Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting
Jiang, Juyong
Wu, Binqing
Chen, Ling
Zhang, Kai
Kim, Sunghun
PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, 2023, : 987 - 996
[4] Detecting unknown HTTP-based malicious communication behavior via generated adversarial flows and hierarchical traffic features
Yun, Xiaochun
Xie, Jiang
Li, Shuhao
Zhang, Yongzheng
Sun, Peishuai
Computers and Security, 2022, 121
[5] Detecting unknown HTTP-based malicious communication behavior via generated adversarial flows and hierarchical traffic features
Yun, Xiaochun
Xie, Jiang
Li, Shuhao
Zhang, Yongzheng
Sun, Peishuai
COMPUTERS & SECURITY, 2022, 121

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