Results 11 to 20 of about 504,342 (225)
Black-box adversarial attacks using evolution strategies [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021 To be published in the proceedings of ACM Genetic and Evolutionary Computation Conference (GECCO) Companion ...
Qiu H., Custode L. L., Iacca G.
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Breaking Cuckoo Hash: Black Box Attacks
IEEE Transactions on Dependable and Secure Computing, 2022 Introduced less than twenty years ago, cuckoo hashing has a number of attractive features like a constant worst case number of memory accesses for queries and close to full memory utilization. Cuckoo hashing has been widely adopted to perform exact matching of an incoming key with a set of stored (key, value) pairs in both software and hardware ...
Pedro Reviriego, Daniel Ting
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SurFree: a fast surrogate-free black-box attack [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 8 ...
Maho, Thibault +2 more
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Simple Black-box Adversarial Attacks
CoRR, 2019 Published at ICML ...
Chuan Guo 0001 +4 more
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Knowledge-enhanced Black-box Attacks for Recommendations
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022 Accepted in the KDD ...
Jingfan Chen +6 more
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GeoDA: A Geometric Framework for Black-Box Adversarial Attacks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Adversarial examples are known as carefully perturbed images fooling image classifiers. We propose a geometric framework to generate adversarial examples in one of the most challenging black-box settings where the adversary can only generate a small number of queries, each of them returning the top-$1$ label of the classifier. Our framework is based on
Ali Rahmati +3 more
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Sparse Black-Box Video Attack with Reinforcement Learning
International Journal of Computer Vision, 2022 Adversarial attacks on video recognition models have been explored recently. However, most existing works treat each video frame equally and ignore their temporal interactions. To overcome this drawback, a few methods try to select some key frames and then perform attacks based on them.
Xingxing Wei 0001 +2 more
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Adversarial Eigen Attack on Black-Box Models
CoRR, 2020 Black-box adversarial attack has attracted a lot of research interests for its practical use in AI safety. Compared with the white-box attack, a black-box setting is more difficult for less available information related to the attacked model and the additional constraint on the query budget.
Linjun Zhou +3 more
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Improving Query Efficiency of Black-Box Adversarial Attack [PDF]
, 2020 Accepted to ...
Yang Bai +5 more
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Generating Adversarial Examples with Adversarial Networks
, 2019 Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mislead DNNs to produce adversary-selected results.
He, Warren +5 more
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