Understanding Real-world Threats to Deep Learning Models in Android Apps

Understanding Real-world Threats to Deep Learning Models in Android Apps

20 September 2022

Papers citing "Understanding Real-world Threats to Deep Learning Models in Android Apps"

19 / 19 papers shown

Title
Offline Model Guard: Secure and Private ML on Mobile Devices Sebastian P. Bayerl Tommaso Frassetto Patrick Jauernig Korbinian Riedhammer A. Sadeghi T. Schneider Emmanuel Stapf Christian Weinert OffRL 44 45 0 05 Jul 2020
Edge Intelligence: Architectures, Challenges, and Applications Dianlei Xu Tong Li Yong Li Xiang Su Sasu Tarkoma Tao Jiang Jon Crowcroft Pan Hui 77 29 0 26 Mar 2020
On the Resilience of Biometric Authentication Systems against Random Inputs Benjamin Zi Hao Zhao Hassan Jameel Asghar M. Kâafar AAML 120 23 0 13 Jan 2020
AI Benchmark: All About Deep Learning on Smartphones in 2019 Andrey D. Ignatov Radu Timofte Andrei Kulik Seungsoo Yang Ke Wang Felix Baum Max Wu Lirong Xu Luc Van Gool ELM 39 220 0 15 Oct 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 87 1,836 0 06 May 2019
Defensive Quantization: When Efficiency Meets Robustness Ji Lin Chuang Gan Song Han MQ 66 203 0 17 Apr 2019
A First Look at Deep Learning Apps on Smartphones Mengwei Xu Jiawei Liu Yuanqiang Liu F. Lin Yunxin Liu Xuanzhe Liu HAI 59 181 0 08 Nov 2018
Rethinking the Value of Network Pruning Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell 36 1,471 0 11 Oct 2018
AI Benchmark: Running Deep Neural Networks on Android Smartphones Andrey D. Ignatov Radu Timofte William Chou Ke Wang Max Wu Tim Hartley Luc Van Gool ELM 65 322 0 02 Oct 2018
Adversarial Robustness Toolbox v1.0.0 Maria-Irina Nicolae M. Sinn Minh-Ngoc Tran Beat Buesser Ambrish Rawat ... Nathalie Baracaldo Bryant Chen Heiko Ludwig Ian Molloy Ben Edwards AAML VLM 69 458 0 03 Jul 2018
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 156 396 0 08 Jun 2018
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference Benoit Jacob S. Kligys Bo Chen Menglong Zhu Matthew Tang Andrew G. Howard Hartwig Adam Dmitry Kalenichenko MQ 136 3,111 0 15 Dec 2017
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 60 105 0 01 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 257 12,029 0 19 Jun 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 90 892 0 01 Mar 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 458 3,138 0 04 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 214 8,533 0 16 Aug 2016
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks Kaipeng Zhang Zhanpeng Zhang Zhifeng Li Yu Qiao CVBM 168 4,954 0 11 Apr 2016
EIE: Efficient Inference Engine on Compressed Deep Neural Network Song Han Xingyu Liu Huizi Mao Jing Pu A. Pedram M. Horowitz W. Dally 118 2,455 0 04 Feb 2016

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