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Attention‐guided black‐box adversarial attacks with large‐scale multiobjective evolutionary optimization
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/int.22258openalex-snapshot
Defense against adversarial attacks by low‐level image transformations
inferredcites →https://doi.org/10.1002/int.22349openalex-snapshot
Camdar‐adv: Generating adversarial patches on 3D object
inferredcites →https://doi.org/10.1002/int.22458openalex-snapshot
Detection defense against adversarial attacks with saliency map
inferredcites →https://doi.org/10.1002/int.22680openalex-snapshot
ELAA: An efficient local adversarial attack using model interpreters
inferredcites →https://doi.org/10.1002/int.22808openalex-snapshot
Attention‐guided transformation‐invariant attack for black‐box adversarial examples
inferredcites →https://doi.org/10.1002/int.22850openalex-snapshot
A data‐driven adversarial examples recognition framework via adversarial feature genomes
inferredcites →https://doi.org/10.1007/978-0-85729-652-8_1openalex-snapshot
Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction
inferredcites →https://doi.org/10.1007/978-3-030-01258-8_10openalex-snapshot
Practical Black-Box Attacks on Deep Neural Networks Using Efficient Query Mechanisms
inferredcites →https://doi.org/10.1007/978-3-030-55304-3_14openalex-snapshot
A Black-Box Attack on Neural Networks Based on Swarm Evolutionary Algorithm
inferredcites →https://doi.org/10.1007/978-3-030-62460-6_52openalex-snapshot
Querying Little Is Enough: Model Inversion Attack via Latent Information
inferredcites →https://doi.org/10.1007/s13042-020-01240-1openalex-snapshot
Generating transferable adversarial examples based on perceptually-aligned perturbation
inferredcites →https://doi.org/10.1007/s13042-020-01242-zopenalex-snapshot
Adversarial examples: attacks and defenses in the physical world
inferredcites →https://doi.org/10.1016/j.cose.2019.04.014openalex-snapshot
POBA-GA: Perturbation optimized black-box adversarial attacks via genetic algorithm
inferredcites →https://doi.org/10.1016/j.cose.2021.102220openalex-snapshot
FineFool: A novel DNN object contour attack on image recognition based on the attention perturbation adversarial technique
inferredcites →https://doi.org/10.1016/j.ins.2008.02.017openalex-snapshot
Large scale evolutionary optimization using cooperative coevolution
inferredcites →https://doi.org/10.1016/j.ins.2020.03.066openalex-snapshot
Adversarial attacks on deep-learning-based radar range profile target recognition
inferredcites →https://doi.org/10.1016/j.jnca.2020.102632openalex-snapshot
Adversarial attacks on deep-learning-based SAR image target recognition
inferredcites →https://doi.org/10.1016/j.neucom.2018.07.080openalex-snapshot
A survey on metaheuristic optimization for random single-hidden layer feedforward neural network
inferredcites →https://doi.org/10.1016/j.neucom.2019.11.051openalex-snapshot
Adversarial attacks on Faster R-CNN object detector
inferredcites →https://doi.org/10.1016/j.neucom.2019.11.052openalex-snapshot
Inspecting adversarial examples using the fisher information
inferredcites →https://doi.org/10.1016/j.neucom.2021.04.062openalex-snapshot
Adversarial defense via self-orthogonal randomization super-network
inferredcites →https://doi.org/10.1016/j.neunet.2019.12.005openalex-snapshot
Efficient network architecture search via multiobjective particle swarm optimization based on decomposition
inferredcites →https://doi.org/10.1016/j.swevo.2011.03.001openalex-snapshot
Multiobjective evolutionary algorithms: A survey of the state of the art
inferredcites →https://doi.org/10.1023/a:1008202821328openalex-snapshot
Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
inferredcites →https://doi.org/10.1109/4235.996017openalex-snapshot
A fast and elitist multiobjective genetic algorithm: NSGA-II
inferredcites →https://doi.org/10.1109/cec.2019.8790123openalex-snapshot
Adversarial Example Generation using Evolutionary Multi-objective Optimization
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2016.282openalex-snapshot
DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/cvpr.2016.319openalex-snapshot
Learning Deep Features for Discriminative Localization
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2018.00957openalex-snapshot
Boosting Adversarial Attacks with Momentum
inferredcites →https://doi.org/10.1109/cvpr.2019.00444openalex-snapshot
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks
inferredcites →https://doi.org/10.1109/cvpr.2019.00668openalex-snapshot
Curls & Whey: Boosting Black-Box Adversarial Attacks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00130openalex-snapshot
QEBA: Query-Efficient Boundary-Based Blackbox Attack
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00847openalex-snapshot
GeoDA: A Geometric Framework for Black-Box Adversarial Attacks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01291openalex-snapshot
Robust Superpixel-Guided Attentional Adversarial Attack
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00196openalex-snapshot
Enhancing the Transferability of Adversarial Attacks through Variance Tuning
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00334openalex-snapshot
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00473openalex-snapshot
Delving into Data: Effectively Substitute Training for Black-box Attack
inferredcites →https://doi.org/10.1109/cvprw.2016.58openalex-snapshot
Adversarial Diversity and Hard Positive Generation
inferredcites →https://doi.org/10.1109/cvprw.2017.172openalex-snapshot
Simple Black-Box Adversarial Attacks on Deep Neural Networks
inferredcites →https://doi.org/10.1109/icassp40776.2020.9053883openalex-snapshot
Deep Neural Networks Based Automatic Speech Recognition for Four Ethiopian Languages
inferredcites →https://doi.org/10.1109/iccv.2019.00137openalex-snapshot
Exploring Randomly Wired Neural Networks for Image Recognition
inferredcites →https://doi.org/10.1109/icpr.2010.579openalex-snapshot
Image Quality Metrics: PSNR vs. SSIM
inferredcites →https://doi.org/10.1109/mci.2017.2742868openalex-snapshot
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
inferredcites →https://doi.org/10.1109/sp.2017.49openalex-snapshot
Towards Evaluating the Robustness of Neural Networks
inferredcites →https://doi.org/10.1109/tcyb.2020.2979930openalex-snapshot
Solving Large-Scale Multiobjective Optimization Problems With Sparse Optimal Solutions via Unsupervised Neural Networks
inferredcites →https://doi.org/10.1109/tdsc.2022.3143566openalex-snapshot
Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy
inferredcites →https://doi.org/10.1109/tevc.2007.892759openalex-snapshot
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
inferredcites →https://doi.org/10.1109/tevc.2013.2281535openalex-snapshot
An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints
inferredcites →https://doi.org/10.1109/tevc.2013.2290086openalex-snapshot
A Survey of Multiobjective Evolutionary Algorithms for Data Mining: Part I
inferredcites →https://doi.org/10.1109/tevc.2016.2519378openalex-snapshot
A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tevc.2016.2608507openalex-snapshot
A Survey of Multiobjective Evolutionary Algorithms based on Decomposition
inferredcites →https://doi.org/10.1109/tevc.2019.2890858openalex-snapshot
One Pixel Attack for Fooling Deep Neural Networks
inferredcites →https://doi.org/10.1109/tevc.2019.2909636openalex-snapshot
A Many-Objective Evolutionary Algorithm With Pareto-Adaptive Reference Points
inferredcites →https://doi.org/10.1109/tevc.2019.2916183openalex-snapshot
Evolving Deep Convolutional Neural Networks for Image Classification
inferredcites →https://doi.org/10.1109/tevc.2019.2918140openalex-snapshot
An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems
inferredcites →https://doi.org/10.1109/tifs.2020.3025438openalex-snapshot
An Automatic Cost Learning Framework for Image Steganography Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/tnnls.2019.2933524openalex-snapshot
Adversarial Examples: Opportunities and Challenges
inferredcites →https://doi.org/10.1109/tpami.2019.2913372openalex-snapshot
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.1145/3052973.3053009openalex-snapshot
Practical Black-Box Attacks against Machine Learning
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3270101.3270106openalex-snapshot
Towards Query Efficient Black-box Attacks
inferredcites →https://doi.org/10.1162/106365600568158openalex-snapshot
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
inferredcites →https://doi.org/10.1162/evco.1995.3.1.1openalex-snapshot
An Overview of Evolutionary Algorithms in Multiobjective Optimization
inferredcites →https://doi.org/10.1201/9781351251389-8openalex-snapshot
Adversarial Examples in the Physical World
inferredcites →https://doi.org/10.1609/aaai.v33i01.3301742openalex-snapshot
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks
inferredcites →https://doi.org/10.3156/jsoft.29.5_177_2openalex-snapshot
GAN（Generative Adversarial Nets）
inferredcites →https://doi.org/10.48550/arxiv.1602.07360openalex-snapshot
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
inferredcites →https://doi.org/10.48550/arxiv.1912.01667openalex-snapshot
A Survey of Black-Box Adversarial Attacks on Computer Vision Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-99-0856-1_30openalex-snapshot
Adversarial Example Defense via Perturbation Grading Strategy
inferred← citeshttps://doi.org/10.1007/s11432-022-3507-7openalex-snapshot
Model architecture level privacy leakage in neural networks
inferred← citeshttps://doi.org/10.1016/j.cose.2022.102947openalex-snapshot
PISA: Pixel skipping-based attentional black-box adversarial attack
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123741openalex-snapshot
A two-stage frequency-domain generation algorithm based on differential evolution for black-box adversarial samples
inferred← citeshttps://doi.org/10.1016/j.ins.2022.08.026openalex-snapshot
GreedyFool: Multi-factor imperceptibility and its application to designing a black-box adversarial attack
inferred← citeshttps://doi.org/10.1016/j.jisa.2023.103675openalex-snapshot
Trustworthy adaptive adversarial perturbations in social networks
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104172openalex-snapshot
Decision attribution and local extremum-guided black-box adversarial attack with adjustable sparsity and discreteness
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3548402openalex-snapshot
Adversarial Examples Detection With Enhanced Image Difference Features Based on Local Histogram Equalization
inferred← citeshttps://doi.org/10.1109/tevc.2025.3623896openalex-snapshot
Turning Sparse Large-Scale Multiobjective Optimization Into Evolutionary Multitasking
inferred← citeshttps://doi.org/10.1360/ssi-2025-0205openalex-snapshot
A detection method against adversarial example attack based on neural network decision boundary and consistency analysis
inferred← citeshttps://doi.org/10.3390/e28060680openalex-snapshot
AMGAA: Attention-Guided Multi-Target Generative Adversarial Attack for Vision Transformers
inferred← citeshttps://doi.org/10.48084/etasr.14980openalex-snapshot
A Crowding Distance-Driven Adaptive Genetic Algorithm with Multiobjective Evolutionary Optimization for Robust Attack Detection
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