Simulating Unknown Target Models For Query Efficient Black Box Attacks

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Details ICICS 2022: Query-Efficient Black-box Adversarial Attack with Random Pattern Noises Update

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Full USENIX Security '20 - Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Update

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[3B] Exploring Model Inversion Attacks in the Black-box Setting

Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction

Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems

GeoDA: A Geometric Framework for Black-Box Adversarial Attacks

Hear “No Evil”, See “Kenansville”: Efficient and Transferable Black-Box Attacks on Automatic ...

Targeted Adversarial Examples for Black Box Audio Systems

ICLR Paper: Sign-OPT: A Query-Efficient Hard-Label Adversarial Attack

1602.02697 - Practical Black Box Attacks against Machine Learning

DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks (Video, ESEC/FSE 2020)

Query Efficient Black Box Adversarial Attacks on Automatic Speech Recognition

Black-Box Attacks | Lecture 18 (Part 2) | Applied Deep Learning (Supplementary)

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Last Updated: October 18, 2026

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Information Hard-Label Based Small Query Black-Box Adversarial Attack Guide

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This a video commentary for the CVPR 2021 paper: Authors: Makoto Yuito, Kenta Suzuki and Kazuki Yoneyama Abstract: Adversarial examples are one of the largest vulnerability of ... Authors: Jeonghwan Park; Paul Miller; Niall McLaughlin Description: We consider the hard-label based Universal 3-Dimensional Perturbations for Authors: Ali Rahmati, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard, Huaiyu Dai Description: Adversarial examples are ... [Full Presentation] Hear “No Evil”, See “Kenansville”: Targeted Adversarial Examples for For AI to be truly trustworthy, we also believe its integrity must be maintained. People need to feel confident that an AI system's ...

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