Fetching the paper…
Reading the bibliography…
To explore the vulnerability of deep neural networks (DNNs), many attack paradigms have been well studied, such as the poisoning-based backdoor attack in the training stage and the adversarial attack in the inference stage.
Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’une classe de problèmes de dirichlet non linéaires
Roland Glowinski and A Marroco · 1975
Earlier work this paper cites.
A dual algorithm for the solution of nonlinear variational problems via finite element approximation
Daniel Gabay and Bertrand Mercier · 1976
Earlier work this paper cites.
Modified lagrangians in convex programming and their generalizations
E Gi Gol’shtein and NV Tret’yakov · 1979
Earlier work this paper cites.
On the douglas—rachford splitting method and the proximal point algorithm for maximal monotone operators
Jonathan Eckstein and Dimitri P Bertsekas · 1992
Earlier work this paper cites.
T-bfa: Targeted bit-flip adversarial weight attack
Adnan Siraj Rakin, Zhezhi He, Jingtao Li, Fan Yao, Chaitali Chakrabarti, and Deliang Fan · 2007
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
How to flip a bit?
Michel Agoyan, Jean-Max Dutertre, Amir-Pasha Mirbaha, David Naccache, Anne-Lise Ribotta, and Assia Tria · 2010
Earlier work this paper cites.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Stephen Boyd, Neal Parikh, and Eric Chu · 2011
Earlier work this paper cites.
Flipping bits in memory without accessing them: An experimental study of dram disturbance errors
Yoongu Kim, Ross Daly, Jeremie Kim, Chris Fallin, Ji Hye Lee, Donghyuk Lee, Chris Wilkerson, Konrad Lai, and Onur Mutlu · 2014
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2014
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Precise laser fault injections into 90 nm and 45 nm sram-cells
Bodo Selmke, Stefan Brummer, Johann Heyszl, and Georg Sigl · 2015
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Drammer: Deterministic rowhammer attacks on mobile platforms
Victor Van Der Veen, Yanick Fratantonio, Martina Lindorfer, Daniel Gruss, Clémentine Maurice, Giovanni Vigna, Herbert Bos, Kaveh Razavi, and Cristiano Giuffrida · 2016
Earlier work this paper cites.
8-bit inference with tensorrt
Szymon Migacz · 2017
Cited alongside, same era.
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
Cited alongside, same era.
Feature squeezing: Detecting adversarial examples in deep neural networks
Weilin Xu, David Evans, and Yanjun Qi · 2017
Cited alongside, same era.
Threat of adversarial attacks on deep learning in computer vision: A survey
Naveed Akhtar and Ajmal Mian · 2018
Cited alongside, same era.
Practical fault attack on deep neural networks
Jakub Breier, Xiaolu Hou, Dirmanto Jap, Lei Ma, Shivam Bhasin, and Yang Liu · 2018
Cited alongside, same era.
Robust physical-world attacks on deep learning visual classification
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, and Dawn Song · 2018
Cited alongside, same era.
Compressing convolutional neural networks via factorized convolutional filters
Tuanhui Li, Baoyuan Wu, Yujiu Yang, Yanbo Fan, Yong Zhang, and Wei Liu · 2019
Later among the works it cites.
Bit-flip attack: Crushing neural network with progressive bit search
Adnan Siraj Rakin, Zhezhi He, and Deliang Fan · 2019
Later among the works it cites.
Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, and Ben Y Zhao · 2019
Later among the works it cites.
Dba: Distributed backdoor attacks against federated learning
Chulin Xie, Keli Huang, Pin-Yu Chen, and Bo Li · 2019
Later among the works it cites.
Exact adversarial attack to image captioning via structured output learning with latent variables
Yan Xu, Baoyuan Wu, Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen, and Wei Liu · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Another flip in the wall of rowhammer defenses
Daniel Gruss, Moritz Lipp, Michael Schwarz, Daniel Genkin, Jonas Juffinger, Sioli O’Connell, Wolfgang Schoechl, and Yuval Yarom · 2018
Cited alongside, same era.
Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, and Dmitry Kalenichenko · 2018
Cited alongside, same era.
Spectral signatures in backdoor attacks
Brandon Tran, Jerry Li, and Aleksander Madry · 2018
Cited alongside, same era.
ℓ p \ell_{p} -box admm: A versatile framework for integer programming
Baoyuan Wu and Bernard Ghanem · 2018
Cited alongside, same era.
Mitigating adversarial effects through randomization
Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, and Alan Yuille · 2018
Cited alongside, same era.
Constrained k-means with general pairwise and cardinality constraints
Adel Bibi, Baoyuan Wu, and Bernard Ghanem · 2019
Cited alongside, same era.
Pu Zhao, Siyue Wang, Cheng Gongye, Yanzhi Wang, Yunsi Fei, and Xue Lin · 2019
Later among the works it cites.
Targeted attack for deep hashing based retrieval
Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-tao Xia, and En-hui Yang · 2020
Later among the works it cites.
Boosting decision-based black-box adversarial attacks with random sign flip
Weilun Chen, Zhaoxiang Zhang, Xiaolin Hu, and Baoyuan Wu · 2020
Later among the works it cites.
Robust anomaly detection and backdoor attack detection via differential privacy
Min Du, Ruoxi Jia, and Dawn Song · 2020
Later among the works it cites.
Sparse adversarial attack via perturbation factorization
Yanbo Fan, Baoyuan Wu, Tuanhui Li, Yong Zhang, Mingyang Li, Zhifeng Li, and Yujiu Yang · 2020
Later among the works it cites.
Adversarial attack on deep product quantization network for image retrieval
Yan Feng, Bin Chen, Tao Dai, and Shutao Xia · 2020
Later among the works it cites.
Defending and harnessing the bit-flip based adversarial weight attack
Zhezhi He, Adnan Siraj Rakin, Jingtao Li, Chaitali Chakrabarti, and Deliang Fan · 2020
Later among the works it cites.
Yiming Li, Baoyuan Wu, Yong Jiang, Zhifeng Li, and Shu-Tao Xia · 2020
Later among the works it cites.
Jonathan Pan · 2020
Later among the works it cites.
Hidden trigger backdoor attacks
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash · 2020
Later among the works it cites.
Deephammer: Depleting the intelligence of deep neural networks through targeted chain of bit flips
Fan Yao, Adnan Siraj Rakin, and Deliang Fan · 2020
Later among the works it cites.