Добірка наукової літератури з теми "Black-box attack"
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Статті в журналах з теми "Black-box attack"
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 джерелаДисертації з теми "Black-box attack"
Sun, Michael(Michael Z. ). "Local approximations of deep learning models for black-box adversarial attacks." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121687.
Повний текст джерелаThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 45-47).
We study the problem of generating adversarial examples for image classifiers in the black-box setting (when the model is available only as an oracle). We unify two seemingly orthogonal and concurrent lines of work in black-box adversarial generation: query-based attacks and substitute models. In particular, we reinterpret adversarial transferability as a strong gradient prior. Based on this unification, we develop a method for integrating model-based priors into the generation of black-box attacks. The resulting algorithms significantly improve upon the current state-of-the-art in black-box adversarial attacks across a wide range of threat models.
by Michael Sun.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Auernhammer, Katja [Verfasser], Felix [Akademischer Betreuer] Freiling, Kolagari Ramin [Akademischer Betreuer] Tavakoli, Felix [Gutachter] Freiling, Kolagari Ramin [Gutachter] Tavakoli, and Dominique [Gutachter] Schröder. "Mask-based Black-box Attacks on Safety-Critical Systems that Use Machine Learning / Katja Auernhammer ; Gutachter: Felix Freiling, Ramin Tavakoli Kolagari, Dominique Schröder ; Felix Freiling, Ramin Tavakoli Kolagari." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2021. http://d-nb.info/1238358292/34.
Повний текст джерелаЧастини книг з теми "Black-box attack"
Cai, Jinghui, Boyang Wang, Xiangfeng Wang, and Bo Jin. "Accelerate Black-Box Attack with White-Box Prior Knowledge." In Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 394–405. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36204-1_33.
Повний текст джерелаBai, Yang, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, and Weiwei Guo. "Improving Query Efficiency of Black-Box Adversarial Attack." In Computer Vision – ECCV 2020, 101–16. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58595-2_7.
Повний текст джерелаAndriushchenko, Maksym, Francesco Croce, Nicolas Flammarion, and Matthias Hein. "Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search." In Computer Vision – ECCV 2020, 484–501. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58592-1_29.
Повний текст джерелаFeng, Xinjie, Hongxun Yao, Wenbin Che, and Shengping Zhang. "An Effective Way to Boost Black-Box Adversarial Attack." In MultiMedia Modeling, 393–404. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37731-1_32.
Повний текст джерелаHuan, Zhaoxin, Yulong Wang, Xiaolu Zhang, Lin Shang, Chilin Fu, and Jun Zhou. "Data-Free Adversarial Perturbations for Practical Black-Box Attack." In Advances in Knowledge Discovery and Data Mining, 127–38. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47436-2_10.
Повний текст джерелаWang, Tong, Yuan Yao, Feng Xu, Shengwei An, Hanghang Tong, and Ting Wang. "An Invisible Black-Box Backdoor Attack Through Frequency Domain." In Lecture Notes in Computer Science, 396–413. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19778-9_23.
Повний текст джерелаPooja, S., and Gilad Gressel. "Towards a General Black-Box Attack on Tabular Datasets." In Lecture Notes in Networks and Systems, 557–67. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1203-2_47.
Повний текст джерелаBayram, Samet, and Kenneth Barner. "A Black-Box Attack on Optical Character Recognition Systems." In Computer Vision and Machine Intelligence, 221–31. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7867-8_18.
Повний текст джерелаYang, Chenglin, Adam Kortylewski, Cihang Xie, Yinzhi Cao, and Alan Yuille. "PatchAttack: A Black-Box Texture-Based Attack with Reinforcement Learning." In Computer Vision – ECCV 2020, 681–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58574-7_41.
Повний текст джерелаYuito, Makoto, Kenta Suzuki, and Kazuki Yoneyama. "Query-Efficient Black-Box Adversarial Attack with Random Pattern Noises." In Information and Communications Security, 303–23. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15777-6_17.
Повний текст джерелаТези доповідей конференцій з теми "Black-box attack"
Chen, Pengpeng, Yongqiang Yang, Dingqi Yang, Hailong Sun, Zhijun Chen, and Peng Lin. "Black-Box Data Poisoning Attacks on Crowdsourcing." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/332.
Повний текст джерелаZhao, Mengchen, Bo An, Wei Gao, and Teng Zhang. "Efficient Label Contamination Attacks Against Black-Box Learning Models." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/551.
Повний текст джерелаJi, Yimu, Jianyu Ding, Zhiyu Chen, Fei Wu, Chi Zhang, Yiming Sun, Jing Sun, and Shangdong Liu. "Simulator Attack+ for Black-Box Adversarial Attack." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897950.
Повний текст джерелаZhang, Yihe, Xu Yuan, Jin Li, Jiadong Lou, Li Chen, and Nian-Feng Tzeng. "Reverse Attack: Black-box Attacks on Collaborative Recommendation." In CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460120.3484805.
Повний текст джерелаWang, Run, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, and Yang Liu. "Amora: Black-box Adversarial Morphing Attack." In MM '20: The 28th ACM International Conference on Multimedia. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3394171.3413544.
Повний текст джерелаXiao, Chaowei, Bo Li, Jun-yan Zhu, Warren He, Mingyan Liu, and Dawn Song. "Generating Adversarial Examples with Adversarial Networks." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/543.
Повний текст джерелаLi, Jie, Rongrong Ji, Hong Liu, Jianzhuang Liu, Bineng Zhong, Cheng Deng, and Qi Tian. "Projection & Probability-Driven Black-Box Attack." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2020. http://dx.doi.org/10.1109/cvpr42600.2020.00044.
Повний текст джерелаWilliams, Phoenix, Ke Li, and Geyong Min. "Black-box adversarial attack via overlapped shapes." In GECCO '22: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3520304.3528934.
Повний текст джерелаMoraffah, Raha, and Huan Liu. "Query-Efficient Target-Agnostic Black-Box Attack." In 2022 IEEE International Conference on Data Mining (ICDM). IEEE, 2022. http://dx.doi.org/10.1109/icdm54844.2022.00047.
Повний текст джерелаMesbah, Abdelhak, Mohamed Mezghiche, and Jean-Louis Lanet. "Persistent fault injection attack from white-box to black-box." In 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B). IEEE, 2017. http://dx.doi.org/10.1109/icee-b.2017.8192164.
Повний текст джерелаЗвіти організацій з теми "Black-box attack"
Ghosh, Anup, Steve Noel, and Sushil Jajodia. Mapping Attack Paths in Black-Box Networks Through Passive Vulnerability Inference. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada563714.
Повний текст джерела