Статті в журналах з теми "Black-box attack"
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Chen, Jinghui, Dongruo Zhou, Jinfeng Yi, and Quanquan Gu. "A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3486–94. http://dx.doi.org/10.1609/aaai.v34i04.5753.
Повний текст джерелаJiang, Yi, and Dengpan Ye. "Black-Box Adversarial Attacks against Audio Forensics Models." Security and Communication Networks 2022 (January 17, 2022): 1–8. http://dx.doi.org/10.1155/2022/6410478.
Повний текст джерелаPark, Hosung, Gwonsang Ryu, and Daeseon Choi. "Partial Retraining Substitute Model for Query-Limited Black-Box Attacks." Applied Sciences 10, no. 20 (October 14, 2020): 7168. http://dx.doi.org/10.3390/app10207168.
Повний текст джерелаZhao, Pu, Pin-yu Chen, Siyue Wang, and Xue Lin. "Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6909–16. http://dx.doi.org/10.1609/aaai.v34i04.6173.
Повний текст джерелаDuan, Mingxing, Kenli Li, Jiayan Deng, Bin Xiao, and Qi Tian. "A Novel Multi-Sample Generation Method for Adversarial Attacks." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 4 (November 30, 2022): 1–21. http://dx.doi.org/10.1145/3506852.
Повний текст джерелаChen, Zhiyu, Jianyu Ding, Fei Wu, Chi Zhang, Yiming Sun, Jing Sun, Shangdong Liu, and Yimu Ji. "An Optimized Black-Box Adversarial Simulator Attack Based on Meta-Learning." Entropy 24, no. 10 (September 27, 2022): 1377. http://dx.doi.org/10.3390/e24101377.
Повний текст джерелаXiang, Fengtao, Jiahui Xu, Wanpeng Zhang, and Weidong Wang. "A Distributed Biased Boundary Attack Method in Black-Box Attack." Applied Sciences 11, no. 21 (November 8, 2021): 10479. http://dx.doi.org/10.3390/app112110479.
Повний текст джерелаWang, Qiuhua, Hui Yang, Guohua Wu, Kim-Kwang Raymond Choo, Zheng Zhang, Gongxun Miao, and Yizhi Ren. "Black-box adversarial attacks on XSS attack detection model." Computers & Security 113 (February 2022): 102554. http://dx.doi.org/10.1016/j.cose.2021.102554.
Повний текст джерелаWang, Lu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and Yuan Jiang. "Spanning attack: reinforce black-box attacks with unlabeled data." Machine Learning 109, no. 12 (October 29, 2020): 2349–68. http://dx.doi.org/10.1007/s10994-020-05916-1.
Повний текст джерелаGao, Xianfeng, Yu-an Tan, Hongwei Jiang, Quanxin Zhang, and Xiaohui Kuang. "Boosting Targeted Black-Box Attacks via Ensemble Substitute Training and Linear Augmentation." Applied Sciences 9, no. 11 (June 3, 2019): 2286. http://dx.doi.org/10.3390/app9112286.
Повний текст джерелаDionysiou, Antreas, Vassilis Vassiliades, and Elias Athanasopoulos. "Exploring Model Inversion Attacks in the Black-box Setting." Proceedings on Privacy Enhancing Technologies 2023, no. 1 (January 2023): 190–206. http://dx.doi.org/10.56553/popets-2023-0012.
Повний текст джерелаKhalel Ibrahem Al-Ubaidy, Mahmood. "BLACK-BOX ATTACK USING NEURO-IDENTIFIER." Cryptologia 28, no. 4 (October 2004): 358–72. http://dx.doi.org/10.1080/0161-110491892980.
Повний текст джерелаTu, Chun-Chen, Paishun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, and Shin-Ming Cheng. "AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 742–49. http://dx.doi.org/10.1609/aaai.v33i01.3301742.
Повний текст джерелаXu, Jiarong, Yizhou Sun, Xin Jiang, Yanhao Wang, Chunping Wang, Jiangang Lu, and Yang Yang. "Blindfolded Attackers Still Threatening: Strict Black-Box Adversarial Attacks on Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 4299–307. http://dx.doi.org/10.1609/aaai.v36i4.20350.
Повний текст джерелаYu, Mengran, and Shiliang Sun. "Natural Black-Box Adversarial Examples against Deep Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8936–44. http://dx.doi.org/10.1609/aaai.v36i8.20876.
Повний текст джерелаKong, Zixiao, Jingfeng Xue, Zhenyan Liu, Yong Wang, and Weijie Han. "MalDBA: Detection for Query-Based Malware Black-Box Adversarial Attacks." Electronics 12, no. 7 (April 6, 2023): 1751. http://dx.doi.org/10.3390/electronics12071751.
Повний текст джерелаChe, Zhaohui, Ali Borji, Guangtao Zhai, Suiyi Ling, Jing Li, and Patrick Le Callet. "A New Ensemble Adversarial Attack Powered by Long-Term Gradient Memories." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3405–13. http://dx.doi.org/10.1609/aaai.v34i04.5743.
Повний текст джерелаWei, Zhipeng, Jingjing Chen, Zuxuan Wu, and Yu-Gang Jiang. "Boosting the Transferability of Video Adversarial Examples via Temporal Translation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 2659–67. http://dx.doi.org/10.1609/aaai.v36i3.20168.
Повний текст джерелаZhang, Qikun, Yuzhi Zhang, Yanling Shao, Mengqi Liu, Jianyong Li, Junling Yuan, and Ruifang Wang. "Boosting Adversarial Attacks with Nadam Optimizer." Electronics 12, no. 6 (March 20, 2023): 1464. http://dx.doi.org/10.3390/electronics12061464.
Повний текст джерелаKoga, Kazuki, and Kazuhiro Takemoto. "Simple Black-Box Universal Adversarial Attacks on Deep Neural Networks for Medical Image Classification." Algorithms 15, no. 5 (April 22, 2022): 144. http://dx.doi.org/10.3390/a15050144.
Повний текст джерелаDu, Xiaohu, Jie Yu, Zibo Yi, Shasha Li, Jun Ma, Yusong Tan, and Qinbo Wu. "A Hybrid Adversarial Attack for Different Application Scenarios." Applied Sciences 10, no. 10 (May 21, 2020): 3559. http://dx.doi.org/10.3390/app10103559.
Повний текст джерелаChitic, Raluca, Ali Osman Topal, and Franck Leprévost. "Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box." Applied Sciences 12, no. 14 (July 21, 2022): 7339. http://dx.doi.org/10.3390/app12147339.
Повний текст джерелаDing, Daizong, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang, and Min Yang. "Black-Box Adversarial Attack on Time Series Classification." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 6 (June 26, 2023): 7358–68. http://dx.doi.org/10.1609/aaai.v37i6.25896.
Повний текст джерелаPark, Sanglee, and Jungmin So. "On the Effectiveness of Adversarial Training in Defending against Adversarial Example Attacks for Image Classification." Applied Sciences 10, no. 22 (November 14, 2020): 8079. http://dx.doi.org/10.3390/app10228079.
Повний текст джерелаWei, Zhipeng, Jingjing Chen, Xingxing Wei, Linxi Jiang, Tat-Seng Chua, Fengfeng Zhou, and Yu-Gang Jiang. "Heuristic Black-Box Adversarial Attacks on Video Recognition Models." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 12338–45. http://dx.doi.org/10.1609/aaai.v34i07.6918.
Повний текст джерелаFu, Zhongwang, and Xiaohui Cui. "ELAA: An Ensemble-Learning-Based Adversarial Attack Targeting Image-Classification Model." Entropy 25, no. 2 (January 22, 2023): 215. http://dx.doi.org/10.3390/e25020215.
Повний текст джерелаLapid, Raz, Zvika Haramaty, and Moshe Sipper. "An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Convolutional Neural Networks." Algorithms 15, no. 11 (October 31, 2022): 407. http://dx.doi.org/10.3390/a15110407.
Повний текст джерелаGuan, Yuting, Junjiang He, Tao Li, Hui Zhao, and Baoqiang Ma. "SSQLi: A Black-Box Adversarial Attack Method for SQL Injection Based on Reinforcement Learning." Future Internet 15, no. 4 (March 30, 2023): 133. http://dx.doi.org/10.3390/fi15040133.
Повний текст джерелаChang, Heng, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, and Junzhou Huang. "A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3389–96. http://dx.doi.org/10.1609/aaai.v34i04.5741.
Повний текст джерелаYang, Bo, Kaiyong Xu, Hengjun Wang, and Hengwei Zhang. "Random Transformation of image brightness for adversarial attack." Journal of Intelligent & Fuzzy Systems 42, no. 3 (February 2, 2022): 1693–704. http://dx.doi.org/10.3233/jifs-211157.
Повний текст джерелаSuryanto, Naufal, Hyoeun Kang, Yongsu Kim, Youngyeo Yun, Harashta Tatimma Larasati, and Howon Kim. "A Distributed Black-Box Adversarial Attack Based on Multi-Group Particle Swarm Optimization." Sensors 20, no. 24 (December 14, 2020): 7158. http://dx.doi.org/10.3390/s20247158.
Повний текст джерелаMaheshwary, Rishabh, Saket Maheshwary, and Vikram Pudi. "Generating Natural Language Attacks in a Hard Label Black Box Setting." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 15 (May 18, 2021): 13525–33. http://dx.doi.org/10.1609/aaai.v35i15.17595.
Повний текст джерелаChen, Yiding, and Xiaojin Zhu. "Optimal Attack against Autoregressive Models by Manipulating the Environment." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3545–52. http://dx.doi.org/10.1609/aaai.v34i04.5760.
Повний текст джерелаCao, Han, Chengxiang Si, Qindong Sun, Yanxiao Liu, Shancang Li, and Prosanta Gope. "ABCAttack: A Gradient-Free Optimization Black-Box Attack for Fooling Deep Image Classifiers." Entropy 24, no. 3 (March 15, 2022): 412. http://dx.doi.org/10.3390/e24030412.
Повний текст джерелаLin, Bin, Jixin Chen, Zhihong Zhang, Yanlin Lai, Xinlong Wu, Lulu Tian, and Wangchi Cheng. "An Adversarial Network-based Multi-model Black-box Attack." Intelligent Automation & Soft Computing 29, no. 3 (2021): 641–49. http://dx.doi.org/10.32604/iasc.2021.016818.
Повний текст джерелаMun, Hyunjun, Sunggwan Seo, Baehoon Son, and Joobeom Yun. "Black-Box Audio Adversarial Attack Using Particle Swarm Optimization." IEEE Access 10 (2022): 23532–44. http://dx.doi.org/10.1109/access.2022.3152526.
Повний текст джерелаHaq, Ijaz Ul, Zahid Younas Khan, Arshad Ahmad, Bashir Hayat, Asif Khan, Ye-Eun Lee, and Ki-Il Kim. "Evaluating and Enhancing the Robustness of Sustainable Neural Relationship Classifiers Using Query-Efficient Black-Box Adversarial Attacks." Sustainability 13, no. 11 (May 24, 2021): 5892. http://dx.doi.org/10.3390/su13115892.
Повний текст джерелаCroce, Francesco, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, and Matthias Hein. "Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (June 28, 2022): 6437–45. http://dx.doi.org/10.1609/aaai.v36i6.20595.
Повний текст джерелаWang, Fangwei, Yuanyuan Lu, Changguang Wang, and Qingru Li. "Binary Black-Box Adversarial Attacks with Evolutionary Learning against IoT Malware Detection." Wireless Communications and Mobile Computing 2021 (August 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/8736946.
Повний текст джерелаFang, Yong, Cheng Huang, Yijia Xu, and Yang Li. "RLXSS: Optimizing XSS Detection Model to Defend Against Adversarial Attacks Based on Reinforcement Learning." Future Internet 11, no. 8 (August 14, 2019): 177. http://dx.doi.org/10.3390/fi11080177.
Повний текст джерелаDu, Meng, Yuxin Sun, Bing Sun, Zilong Wu, Lan Luo, Daping Bi, and Mingyang Du. "TAN: A Transferable Adversarial Network for DNN-Based UAV SAR Automatic Target Recognition Models." Drones 7, no. 3 (March 16, 2023): 205. http://dx.doi.org/10.3390/drones7030205.
Повний текст джерелаWang, Fangwei, Zerou Ma, Xiaohan Zhang, Qingru Li, and Changguang Wang. "DDSG-GAN: Generative Adversarial Network with Dual Discriminators and Single Generator for Black-Box Attacks." Mathematics 11, no. 4 (February 16, 2023): 1016. http://dx.doi.org/10.3390/math11041016.
Повний текст джерелаSauka, Kudzai, Gun-Yoo Shin, Dong-Wook Kim, and Myung-Mook Han. "Adversarial Robust and Explainable Network Intrusion Detection Systems Based on Deep Learning." Applied Sciences 12, no. 13 (June 25, 2022): 6451. http://dx.doi.org/10.3390/app12136451.
Повний текст джерелаIlham Firdaus, Januar Al Amien, and Soni Soni. "String Matching untuk Mendeteksi Serangan Sniffing (ARP Spoofing) pada IDS Snort." Jurnal CoSciTech (Computer Science and Information Technology) 1, no. 2 (October 31, 2020): 44–49. http://dx.doi.org/10.37859/coscitech.v1i2.2180.
Повний текст джерелаZhang, Yue, Seong-Yoon Shin, Xujie Tan, and Bin Xiong. "A Self-Adaptive Approximated-Gradient-Simulation Method for Black-Box Adversarial Sample Generation." Applied Sciences 13, no. 3 (January 18, 2023): 1298. http://dx.doi.org/10.3390/app13031298.
Повний текст джерелаBai, Yang, Yisen Wang, Yuyuan Zeng, Yong Jiang, and Shu-Tao Xia. "Query efficient black-box adversarial attack on deep neural networks." Pattern Recognition 133 (January 2023): 109037. http://dx.doi.org/10.1016/j.patcog.2022.109037.
Повний текст джерелаLi, Siyuan, Guangji Huang, Xing Xu, and Huimin Lu. "Query-based black-box attack against medical image segmentation model." Future Generation Computer Systems 133 (August 2022): 331–37. http://dx.doi.org/10.1016/j.future.2022.03.008.
Повний текст джерелаDing, Kangyi, Xiaolei Liu, Weina Niu, Teng Hu, Yanping Wang, and Xiaosong Zhang. "A low-query black-box adversarial attack based on transferability." Knowledge-Based Systems 226 (August 2021): 107102. http://dx.doi.org/10.1016/j.knosys.2021.107102.
Повний текст джерелаZhu, Jiaqi, Feng Dai, Lingyun Yu, Hongtao Xie, Lidong Wang, Bo Wu, and Yongdong Zhang. "Attention‐guided transformation‐invariant attack for black‐box adversarial examples." International Journal of Intelligent Systems 37, no. 5 (January 11, 2022): 3142–65. http://dx.doi.org/10.1002/int.22808.
Повний текст джерелаWang, Yajie, Yu-an Tan, Wenjiao Zhang, Yuhang Zhao, and Xiaohui Kuang. "An adversarial attack on DNN-based black-box object detectors." Journal of Network and Computer Applications 161 (July 2020): 102634. http://dx.doi.org/10.1016/j.jnca.2020.102634.
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