1. 长沙民政职业技术学院软件学院
2. 长沙理工大学电气与信息工程学院
纸质出版:2025
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杨洪朝, 谢英辉, 张占, 等. 基于深度神经网络的低时延的入侵检测模型[J]. 传感器与微系统, 2025,(3):84-88.
杨洪朝, 谢英辉, 张占, 等. 基于深度神经网络的低时延的入侵检测模型[J]. 传感器与微系统, 2025,(3):84-88. DOI: 10.13873/J.1000-9787(2025)03-0084-05.
为适应物联网(IoT)节点计算能力不足和易受网络攻击等特点,提出融合生成对抗网络(GAN)和长短期记忆网络(LSTM)的低时延的入侵检测模型(GAN-LLD)
使模型更好适应IoT对资源的苛刻需求。GAN-LLD模型采用雾结构,将检测模型部署在雾层,进而满足低检测时延要求。为了获取更高的检测率,GAN-LLD模型引入重构损失,通过将数据样本映射至潜在空间,再计算重构损失。最后,利用数据集NSL-KDD验证GAN-LLD模型的性能。仿真结果表明,相比于多变量异常检测(MAD)-GAN模型,提出的GAN-LLD模型具有高的检测率和低的检测时延。
李聪宇,赵利辉,安洋.基于图神经网络的物联网入侵检测研究[J].中北大学学报(自然科学版),2024(02).
项睿涵,潘巨龙,李玲艺,方堃.一种物联网入侵检测和成员推理攻击研究[J].传感技术学报,2024(02).
吴昊,郝佳佳,卢云龙.物联网场景下基于蜜场的分布式网络入侵检测系统研究[J].通信学报,2024(01).
刘拥民,张钱垒,杨钰津,罗皓懿,黄浩.新型GAN的WSN异常检测方法[J].计算机工程与设计,2023(12).
郭志涛,魏英杰,陈中林,杨玉杰.基于树莓派的海上风电环境及设备监测系统设计[J].传感器与微系统,2023(08).
李萌萌,马力,贾宇峰.模式搜索星型生成对抗网络下的面部表情生成[J].传感器与微系统,2022(07).
宁正,牛宏侠,张肇鑫.基于改进混合高斯模型的铁轨异物入侵检测方法[J].传感器与微系统,2021(05).
Wahab Omar Abdel,Bentahar Jamal,Otrok Hadi,Mourad Azzam.Optimal Load Distribution for the Detection of VM-Based DDoS Attacks in the Cloud[J].IEEE Transactions on Services Computing,2020.
Hyunseung Choi,Mintae Kim,Gyubok Lee,Wooju Kim.Unsupervised learning approach for network intrusion detection system using autoencoders[J].The Journal of Supercomputing,2019.
Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria,Christian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University Vienna, Austria. Electronic address: https://www.github.com/tSchlegl/f-AnoGAN.,Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria,Christian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University Vienna, Austria.,Christian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University Vienna, Austria.,Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria. Electronic address: http://www.cir.meduniwien.ac.at.,Christian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University Vienna, Austria..f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks[J].Medical Image Analysis,2019.
Abeshu Abebe,Chilamkurti Naveen.Deep Learning: The Frontier for Distributed Attack Detection in Fog-to-Things Computing[J].IEEE Communications Magazine,2018.
Li Jianhua,Jin Jiong,Yuan Dong,Zhang Hongke.Virtual Fog: A Virtualization Enabled Fog Computing Framework for Internet of Things[J].IEEE Internet of Things Journal,2018.
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