Journal of Computer Applications ›› 2024, Vol. 44 ›› Issue (8): 2521-2527.DOI: 10.11772/j.issn.1001-9081.2023081165
• Network and communications • Previous Articles Next Articles
Rui SHI1,2(), Yong LI2, Yanhan ZHU1,2
Received:
2023-08-31
Revised:
2023-10-31
Accepted:
2023-11-14
Online:
2024-08-22
Published:
2024-08-10
Contact:
Rui SHI
About author:
LI Yong, born in 1977, Ph. D., associate research fellow. His research interests include anti-jamming of wireless communication.Supported by:
通讯作者:
石锐
作者简介:
石锐(1999—),男,江苏兴化人,硕士研究生,主要研究方向:深度神经网络、无线通信智能抗干扰 1164852907@qq.com基金资助:
CLC Number:
Rui SHI, Yong LI, Yanhan ZHU. Adversarial sample attack algorithm of modulation signal based on equalization of feature gradient[J]. Journal of Computer Applications, 2024, 44(8): 2521-2527.
石锐, 李勇, 朱延晗. 基于特征梯度均值化的调制信号对抗样本攻击算法[J]. 《计算机应用》唯一官方网站, 2024, 44(8): 2521-2527.
Add to citation manager EndNote|Ris|BibTeX
URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2023081165
算法 | 时间 | 算法 | 时间 |
---|---|---|---|
FGSM | 0.12 | PGD | 0.78 |
I-FGSM | 0.81 | EFG-MI-FGSM | 1.48 |
MI-FGSM | 0.90 |
Tab. 1 Running time of white box attack on VTCNN2
算法 | 时间 | 算法 | 时间 |
---|---|---|---|
FGSM | 0.12 | PGD | 0.78 |
I-FGSM | 0.81 | EFG-MI-FGSM | 1.48 |
MI-FGSM | 0.90 |
1 | 季长清,高志勇,秦静,等.基于卷积神经网络的图像分类算法综述[J].计算机应用,2022, 42(4): 1044-1049. |
JI C Q, GAO Z Y, QIN J, et al. Review of image classification algorithms based on convolutional neural networks[J]. Journal of Computer Applications,2022, 42(4): 1044-1049. | |
2 | 冯志伟.神经网络、深度学习与自然语言处理[J].上海师范大学学报(哲学社会科学版),2021, 50(2): 110-122. |
FENG Z W. Artificial neural network, deep learning, and natural language processing[J]. Journal of Shanghai Normal University (Philosophy & Social Sciences Edition),2021, 50(2): 110-122. | |
3 | 李思敏, 谷宇, 张宝华, 等. 基于改进ResNeXt的肺癌病理图像分类[J]. 计算机工程与设计, 2023, 44(8): 2439-2446. |
LI S M, GU Y, ZHANG B H, et al. Lung cancer pathological image classification based on improved ResNeXt[J]. Computer Engineering and Design, 2023, 44(8): 2439-2446. | |
4 | 张开生,赵小芬. 复杂环境下自适应深度神经网络的鲁棒语音识别[J]. 计算机工程与科学, 2022, 44(6): 1105-1113. |
ZHANG K S, ZHAO X F. Robust speech recognition based on adaptive deep neural network in complex environment[J]. Computer Engineering & Science,2022, 44(6): 1105-1113. | |
5 | 梁应敞,谭俊杰, NIYATO D.智能无线通信技术研究概况[J].通信学报,2020, 41(7): 1-17. |
LIANG Y C, TAN J J, NIYATO D. Overview on intelligent wireless communication technology[J]. Journal on Communications,2020, 41(7): 1-17. | |
6 | XIE X, NI Y, PENG S, et al. Deep learning based automatic modulation classification for varying SNR environment[C]// Proceedings of the 2019 28th Wireless and Optical Communications Conference. Piscataway: IEEE, 2019: 1-5. |
7 | 陈梦轩,张振永,纪守领,等.图像对抗样本研究综述[J].计算机科学, 2022, 49(2): 92-106. |
CHEN M X, ZHANG Z Y, JI S L, et al. Survey of research progress on adversarial examples in images[J]. Computer Science, 2022, 49(2): 92-106. | |
8 | YU J A, PENG L. Black-box attacks on DNN classifier based on fuzzy adversarial examples[C]// Proceedings of the 2020 IEEE 5th International Conference on Signal and Image Processing. Piscataway:IEEE, 2020: 965-969. |
9 | 胡明雪,王磊, ZERWAS J.基于遗传算法的数据中心流量对抗样本生成方法[J].计算机应用, 2022, 42(): 146-151. |
HU M X, WANG L, ZERWAS J. Data center traffic adversarial samples generation method based on genetic algorithm[J].Journal of Computer Applications, 2022, 42(S1): 146-151. | |
10 | YANG X, LIN J, ZHANG H, et al. Improving the transferability of adversarial examples via direction tuning[J].Information Sciences,2023, 647: 119491. |
11 | LIU Y, LIU Y, YANG C. Modulation recognition with graph convolutional network[J]. IEEE Wireless Communications Letters, 2020, 9(5): 624-627. |
12 | O’SHEA T J, CORGAN J, CLANCY T C. Convolutional radio modulation recognition networks[C]// Proceedings of the 17th International Conference on Engineering Applications of Neural Networks. Cham: Springer, 2016: 213-226. |
13 | MENG F, CHEN P, WU L. Automatic modulation classification: a deep learning enabled approach[J]. IEEE Transactions on Vehicular Technology, 2018, 67(11): 10760-10772. |
14 | 翁建新,赵知劲,占锦敏.利用并联CNN-LSTM的调制样式识别算法[J].信号处理, 2019, 35(5): 870-876. |
WENG J X, ZHAO Z J, ZHAN J M. Modulation recognition algorithm by using parallel CNN-LSTM[J]. Journal of Signal Processing, 2019, 35(5): 870-876. | |
15 | 庞伊琼,许华,蒋磊,等.基于元学习的小样本调制识别算法[J].空军工程大学学报(自然科学版), 2022, 23(5): 77-82. |
PANG Y Q, XU H, JIANG L, et al. A few-shot modulation recognition algorithm based on meta-learning[J].Journal of Air Force Engineering University, 2022, 23(5): 77-82. | |
16 | JEONG S, LEE U, KIM S C. Spectrogram-based automatic modulation recognition using convolution neural network[C]// Proceedings of 2018 10th International Conference on Ubiquitous and Future Networks. Piscataway: IEEE, 2018: 843-845. |
17 | LI Y, SHAO G, WANG B. Automatic modulation classification based on bispectrum and CNN[C]// Proceedings of 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference. Piscataway: IEEE, 2019:311-316. |
18 | KHAN F N, ZHONG K, AL-ARASHI W H, et al. Modulation format identification in coherent receivers using deep machine learning[J]. IEEE Photonics Technology Letters, 2016, 28(17): 1886-1889. |
19 | 李红光,郭英,眭萍,等.基于时频特征的卷积神经网络跳频调制识别[J].浙江大学学报(工学版), 2020, 54(10): 1945-1954. |
LI H G, GUO Y, SUI P, et al. Frequency hopping modulation recognition of convolutional neural network based on time-frequency characteristics[J].Journal of Zhejiang University (Engineering Science), 2020, 54(10): 1945-1954. | |
20 | SZEGEDY C, ZAREMBA W, SUTSKEVER I, et al. Intriguing properties of neural networks[EB/OL].(2014-02-19)[2023-08-20].. |
21 | 闫嘉乐,徐洋,张思聪,等.图像分类模型的对抗样本攻防研究综述[J].计算机工程与应用,2022, 58(23): 24-41. |
YAN J L, XU Y, ZHANG S C, et al. Survey of research on adversarial examples attack and defense in image classification model[J].Computer Engineering and Applications,2022, 58(23): 24-41. | |
22 | GOODFELLOW I J, SHLENS J, SZEGEDY C. Explaining and harnessing adversarial examples[EB/OL].(2015-03-20)[2023-08-20].. |
23 | KURAKIN A, GOODFELLOW I, BENGIO S. Adversarial examples in the physical world[EB/OL].(2017-02-11)[2023-08-20].. |
24 | DONG Y, LIAO F, PANG T, et al. Boosting adversarial attacks with momentum[C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 9185-9193. |
25 | MADRY A, MAKELOV A, SCHMIDT L, et al. Towards deep learning models resistant to adversarial attacks[EB/OL].(2019-09-04)[2023-08-20].. |
26 | SADEGHI M, LARSSON E G. Adversarial attacks on deep learning based radio signal classification[J]. IEEE Wireless Communications Letters, 2019, 8(1): 213-216. |
27 | ZHAO H, LIN Y, GAO S, et al. Evaluating and improving adversarial attacks on DNN-based modulation recognition[C]// Proceedings of 2020 IEEE Global Communications Conference. Piscataway:IEEE,2020:1-5. |
28 | 陶明亮,唐舒婷,王伶.面向智能调制识别的电磁信号灵巧诱骗方法[J].信号处理, 2022, 38(12): 2496-2506. |
TAO M L, TANG S T, WANG L. Radio signal smart deception method for intelligent modulation classification[J].Journal of Signal Processing,2022, 38(12): 2496-2506. | |
29 | KIM B, SAGDUYU Y E, DAVASLIOGLU K, et al. Channel-aware adversarial attacks against deep learning-based wireless signal classifiers[J]. IEEE Transactions on Wireless Communications,2022, 21(6): 3868-3880. |
30 | XIE H, TAN J, ZHANG X Y, et al. Low-interception waveform: to prevent the recognition of spectrum waveform modulation via adversarial example[C]// Proceedings of 2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science. Piscataway: IEEE, 2021: 1-4. |
[1] | Mengmei YAN, Dongping YANG. Review of mean field theory for deep neural network [J]. Journal of Computer Applications, 2024, 44(2): 331-343. |
[2] | Yunfei SHEN, Fei SHEN, Fang LI, Jun ZHANG. Deep neural network model acceleration method based on tensor virtual machine [J]. Journal of Computer Applications, 2023, 43(9): 2836-2844. |
[3] | Xujian ZHAO, Hanglin LI. Deep neural network compression algorithm based on hybrid mechanism [J]. Journal of Computer Applications, 2023, 43(9): 2686-2691. |
[4] | Xiaolin LI, Songjia YANG. Hybrid beamforming for multi-user mmWave relay networks using deep learning [J]. Journal of Computer Applications, 2023, 43(8): 2511-2516. |
[5] | Haiyu YANG, Wenpu GUO, Kai KANG. Signal modulation recognition method based on convolutional long short-term deep neural network [J]. Journal of Computer Applications, 2023, 43(4): 1318-1322. |
[6] | Jici ZHANG, Chunlong FAN, Cailong LI, Xuedong ZHENG. Cross-model universal perturbation generation method based on geometric relationship [J]. Journal of Computer Applications, 2023, 43(11): 3428-3435. |
[7] | GAO Yuanyuan, YU Zhenhua, DU Fang, SONG Lijuan. Unlabeled network pruning algorithm based on Bayesian optimization [J]. Journal of Computer Applications, 2023, 43(1): 30-36. |
[8] | LIU Xiaoyu, CHEN Huaixin, LIU Biyuan, LIN Ying, MA Teng. License plate detection algorithm in unrestricted scenes based on adaptive confidence threshold [J]. Journal of Computer Applications, 2023, 43(1): 67-73. |
[9] | Wentao MAO, Guifang WU, Chao WU, Zhi DOU. Animation video generation model based on Chinese impressionistic style transfer [J]. Journal of Computer Applications, 2022, 42(7): 2162-2169. |
[10] | Meng YU, Wentao HE, Xuchuan ZHOU, Mengtian CUI, Keqi WU, Wenjie ZHOU. Review of recommendation system [J]. Journal of Computer Applications, 2022, 42(6): 1898-1913. |
[11] | Quan CHEN, Li LI, Yongle CHEN, Yuexing DUAN. Adversarial attack algorithm for deep learning interpretability [J]. Journal of Computer Applications, 2022, 42(2): 510-518. |
[12] | Anyi WANG, Heng ZHANG. Multi-input multi-output intelligent receiver model based on multi-label classification algorithm [J]. Journal of Computer Applications, 2022, 42(10): 3124-3129. |
[13] | CHEN Chengrui, SUN Ning, HE Shibiao, LIAO Yong. Deep learning-based joint channel estimation and equalization algorithm for C-V2X communications [J]. Journal of Computer Applications, 2021, 41(9): 2687-2693. |
[14] | WANG Shuyan, HOU Zeyu, SUN Jiaze. Difference detection method of adversarial samples oriented to deep learning [J]. Journal of Computer Applications, 2021, 41(7): 1849-1856. |
[15] | ZHANG Mingming, LU Qingning, LI Wenzhong, SONG Hu. Deep neural network compression algorithm based on combined dynamic pruning [J]. Journal of Computer Applications, 2021, 41(6): 1589-1596. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||