{"total":33,"rows":[{"id":"2205.13152","title":"Transferable Adversarial Attack based on Integrated Gradients","created":"2022-05-26","cited_by_count":35,"area":null},{"id":"2111.09961","title":"A Review of Adversarial Attack and Defense for Classification Methods","created":"2021-11-18","cited_by_count":29,"area":null},{"id":"2301.00364","title":"Generalizable Black-Box Adversarial Attack with Meta Learning","created":"2023-01-01","cited_by_count":29,"area":null},{"id":"2304.13410","title":"Improving Adversarial Transferability via Intermediate-level Perturbation Decay","created":"2023-04-26","cited_by_count":29,"area":null},{"id":"2103.02927","title":"QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval","created":"2021-03-04","cited_by_count":22,"area":null},{"id":"2302.09457","title":"Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective","created":"2023-02-19","cited_by_count":20,"area":null},{"id":"2102.08168","title":"Just Noticeable Difference for Deep Machine Vision","created":"2021-02-16","cited_by_count":19,"area":null},{"id":"2205.12134","title":"Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks","created":"2022-05-24","cited_by_count":19,"area":null},{"id":"2310.00633","title":"A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks","created":"2023-10-01","cited_by_count":19,"area":null},{"id":"2203.08725","title":"Attacking deep networks with surrogate-based adversarial black-box methods is easy","created":"2022-03-16","cited_by_count":18,"area":null},{"id":"2101.04829","title":"On the Effectiveness of Small Input Noise for Defending Against Query-based Black-Box Attacks","created":"2021-01-13","cited_by_count":17,"area":null},{"id":"2405.19098","title":"Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior","created":"2024-05-29","cited_by_count":11,"area":null},{"id":"2107.11275","title":"A Differentiable Language Model Adversarial Attack on Text Classifiers","created":"2021-07-23","cited_by_count":9,"area":null},{"id":"2203.04607","title":"Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation","created":"2022-03-09","cited_by_count":9,"area":null},{"id":"2203.10723","title":"An Intermediate-level Attack Framework on The Basis of Linear Regression","created":"2022-03-21","cited_by_count":9,"area":null},{"id":"2302.04477","title":"An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint","created":"2023-02-09","cited_by_count":9,"area":null},{"id":"2106.06056","title":"Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation","created":"2021-06-10","cited_by_count":8,"area":null},{"id":"2111.01714","title":"Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks","created":"2021-11-02","cited_by_count":7,"area":null},{"id":"2310.17534","title":"SoK: Pitfalls in Evaluating Black-Box Attacks","created":"2023-10-26","cited_by_count":6,"area":null},{"id":"2106.15357","title":"Multi-stage Optimization based Adversarial Training","created":"2021-06-26","cited_by_count":4,"area":null},{"id":"2203.13779","title":"Origins of Low-dimensional Adversarial Perturbations","created":"2022-03-25","cited_by_count":4,"area":null},{"id":"2105.15010","title":"Query Attack by Multi-Identity Surrogates","created":"2021-05-31","cited_by_count":3,"area":null},{"id":"2105.08620","title":"Adversarial Examples Detection with Bayesian Neural Network","created":"2021-05-18","cited_by_count":2,"area":null},{"id":"2109.04300","title":"Energy Attack: On Transferring Adversarial Examples","created":"2021-09-09","cited_by_count":2,"area":null},{"id":"2406.03017","title":"DifAttack++: Query-Efficient Black-Box Adversarial Attack via Hierarchical Disentangled Feature Space in Cross-Domain","created":"2024-06-05","cited_by_count":2,"area":null},{"id":"2503.12827","title":"GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack","created":"2025-03-17","cited_by_count":2,"area":null},{"id":"2111.04371","title":"Geometrically Adaptive Dictionary Attack on Face Recognition","created":"2021-11-08","cited_by_count":1,"area":null},{"id":"2309.14585","title":"DifAttack: Query-Efficient Black-Box Attack via Disentangled Feature Space","created":"2023-09-26","cited_by_count":1,"area":null},{"id":"2401.14031","title":"Sparse and Transferable Universal Singular Vectors Attack","created":"2024-01-25","cited_by_count":1,"area":null},{"id":"2102.07360","title":"Generating Structured Adversarial Attacks Using Frank-Wolfe Method","created":"2021-02-15","cited_by_count":0,"area":null},{"id":"2203.04405","title":"Art-Attack: Black-Box Adversarial Attack via Evolutionary Art","created":"2022-03-07","cited_by_count":0,"area":null},{"id":"2208.13182","title":"Cross-domain Cross-architecture Black-box Attacks on Fine-tuned Models with Transferred Evolutionary Strategies","created":"2022-08-28","cited_by_count":0,"area":null},{"id":"2507.07259","title":"Exploiting Edge Features for Transferable Adversarial Attacks in Distributed Machine Learning","created":"2025-07-09","cited_by_count":0,"area":null}],"next_cursor":null}