[1] |
化存卿 . 物联网安全检测与防护机制综述[J]. 上海交通大学学报, 2018,52(10): 1307-1313.
|
|
HUA C Q . A survey of security detection and protection for Internet of things[J]. Journal of Shanghai Jiao Tong University, 2018,52(10): 1307-1313.
|
[2] |
POPOOLA S I , ANDE R , ADEBISI B ,et al. Federated deep learning for zero-day botnet attack detection in IoT-edge devices[J]. IEEE Internet of Things Journal, 2022,9(5): 3930-3944.
|
[3] |
霍添财 . 物联网终端设备恶意软件检测研究与设计[D]. 西安:西安电子科技大学, 2021.
|
|
HUO T C . Research and design of malware detection of terminal devices in IoT networks[D]. Xi’an:Xidian University, 2021.
|
[4] |
彭安妮, 周威, 贾岩 ,等. 物联网操作系统安全研究综述[J]. 通信学报, 2018,39(3): 22-34.
|
|
PENG A N , ZHOU W , JIA Y ,et al. Survey of the Internet of things operating system security[J]. Journal on Communications, 2018,39(3): 22-34.
|
[5] |
STOYANOVA M , NIKOLOUDAKIS Y , PANAGIOTAKIS S ,et al. A survey on the Internet of things (IoT) forensics:challenges,approaches,and open issues[J]. IEEE Communications Surveys & Tutorials, 2020,22(2): 1191-1221.
|
[6] |
张玉清, 周威, 彭安妮 . 物联网安全综述[J]. 计算机研究与发展, 2017,54(10): 2130-2143.
|
|
ZHANG Y Q , ZHOU W , PENG A N . Survey of Internet of things security[J]. Journal of Computer Research and Development, 2017,54(10): 2130-2143.
|
[7] |
梁浩然, 伍军, 赵程程 ,等. 基于博弈优化边缘学习的物联网入侵检测研究[J]. 物联网学报, 2021,5(2): 37-47.
|
|
LIANG H R , WU J , ZHAO C C ,et al. Leveraging edge learning and game theory for intrusion detection in Internet of things[J]. Chinese Journal on Internet of Things, 2021,5(2): 37-47.
|
[8] |
林冲, 闫文君, 张立民 ,等. 通信信号调制识别综述[J]. 中国电子科学研究院学报, 2021,16(11): 1074-1085.
|
|
LIN C , YAN W J , ZHANG L M ,et al. An overview of communication signals modulation recognition[J]. Journal of China Academy of Electronics and Information Technology, 2021,16(11): 1074-1085.
|
[9] |
代翱, 张海剑, 孙洪 . 联合时域和时频域特征的数字调制信号自动分类[J]. 信号处理, 2016,32(11): 1283-1292.
|
|
DAI A , ZHANG H J , SUN H . Digital modulations automatic classification using the combination of several features extracted from time and time-frequence domain[J]. Journal of Signal Processing, 2016,32(11): 1283-1292.
|
[10] |
向建, 高勇 . 基于GRU-CNN并联神经网络的自动调制识别[J]. 电讯技术, 2021,61(11): 1339-1343.
|
|
XIANG J , GAO Y . Automatic modulation recognition based on GRU-CNN parallel neural network[J]. Telecommunication Engineering, 2021,61(11): 1339-1343.
|
[11] |
桂冠, 王禹, 黄浩 . 基于深度学习的物理层无线通信技术:机遇与挑战[J]. 通信学报, 2019,40(2): 19-23.
|
|
GUI G , WANG Y , HUANG H . Deep learning based physical layer wireless communication techniques:opportunities and challenges[J]. Journal on Communications, 2019,40(2): 19-23.
|
[12] |
XU J L , LUO C B , PARR G ,et al. A spatiotemporal multi-channel learning framework for automatic modulation recognition[J]. IEEE Wireless Communications Letters, 2020,9(10): 1629-1632.
|
[13] |
ZHANG Z F , LUO H , WANG C ,et al. Automatic modulation classification using CNN-LSTM based dual-stream structure[J]. IEEE Transactions on Vehicular Technology, 2020,69(11): 13521-13531.
|
[14] |
ZHANG F X , LUO C B , XU J L ,et al. An efficient deep learning model for automatic modulation recognition based on parameter estimation and transformation[J]. IEEE Communications Letters, 2021,25(10): 3287-3290.
|
[15] |
HUYNH-THE T , HUA C H , PHAM Q V ,et al. MCNet:an efficient CNN architecture for robust automatic modulation classification[J]. IEEE Communications Letters, 2020,24(4): 811-815.
|
[16] |
张立志, 冉浙江, 赖志权 ,等. 分布式深度学习通信架构的性能分析[J]. 计算机工程与科学, 2021,43(3): 416-425.
|
|
ZHANG L Z , RAN Z J , LAI Z Q ,et al. Performance analysis of distributed deep learning communication architecture[J]. Computer Engineering & Science, 2021,43(3): 416-425.
|
[17] |
刘艺璇, 陈红, 刘宇涵 ,等. 联邦学习中的隐私保护技术[J]. 软件学报, 2022,33(3): 1057-1092.
|
|
LIU Y X , CHEN H , LIU Y H ,et al. Privacy-preserving techniques in federated learning[J]. Journal of Software, 2022,33(3): 1057-1092.
|
[18] |
陈世达, 刘强, 韩亮 . 降低分布式训练通信的梯度稀疏压缩方法[J]. 浙江大学学报(工学版), 2021,55(2): 386-394.
|
|
CHEN S D , LIU Q , HAN L . Gradient sparsification compression approach to reducing communication in distributed training[J]. Journal of Zhejiang University (Engineering Science), 2021,55(2): 386-394.
|
[19] |
赵羽, 杨洁, 刘淼 ,等. 面向视频监控基于联邦学习的智能边缘计算技术[J]. 通信学报, 2020,41(10): 109-115.
|
|
ZHAO Y , YANG J , LIU M ,et al. Federated learning based intelligent edge computing technique for video surveillance[J]. Journal on Communications, 2020,41(10): 109-115.
|
[20] |
WANG Y , GUO L , ZHAO Y ,et al. Distributed learning for automatic modulation classification in edge devices[J]. IEEE Wireless Communications Letters, 2020,9(12): 2177-2181.
|