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Adversarial Attacks on Image Classification Models: FGSM and Patch Attacks and Their Impact

https://doi.org/10.5772/intechopen.112442

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-40994-3_25openalex-snapshot

Evasion Attacks against Machine Learning at Test Time

inferredcites →https://doi.org/10.1016/j.neunet.2012.02.023openalex-snapshot

Multi-column deep neural network for traffic sign classification

inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot

ImageNet: A large-scale hierarchical image database

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

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.2016.90openalex-snapshot

Deep Residual Learning for Image Recognition

inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot

Densely Connected Convolutional Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00175openalex-snapshot

Robust Physical-World Attacks on Deep Learning Visual Classification

inferredcites →https://doi.org/10.1109/cvpr42600.2020.00040openalex-snapshot

Benchmarking Adversarial Robustness on Image Classification

inferredcites →https://doi.org/10.1109/eurosp.2016.36openalex-snapshot

The Limitations of Deep Learning in Adversarial Settings

inferredcites →https://doi.org/10.1109/hpcc-dss-smartcity-dependsys57074.2022.00255openalex-snapshot

A Block Gray Adversarial Attack Method for Image Classification Neural Network

inferredcites →https://doi.org/10.1109/icisfall51598.2021.9627468openalex-snapshot

An Efficient Attention Based Image Adversarial Attack Algorithm with Differential Evolution on Realistic High-Resolution Image

inferredcites →https://doi.org/10.1109/icivc55077.2022.9886997openalex-snapshot

Adversarial Attacks and Defenses in Image Classification: A Practical Perspective

inferredcites →https://doi.org/10.1109/ijcb.2011.6117503openalex-snapshot

Counter-measures to photo attacks in face recognition: A public database and a baseline

inferredcites →https://doi.org/10.1109/ijcnn52387.2021.9533495openalex-snapshot

Adversarial Attacks and Defense on Deep Learning Classification Models using YCbCr Color Images

inferredcites →https://doi.org/10.1109/tip.2021.3118977openalex-snapshot

Self-Attention Context Network: Addressing the Threat of Adversarial Attacks for Hyperspectral Image Classification

inferredcites →https://doi.org/10.1142/s0218001414600027openalex-snapshot

PATTERN RECOGNITION SYSTEMS UNDER ATTACK: DESIGN ISSUES AND RESEARCH CHALLENGES

inferredcites →https://doi.org/10.1145/1180405.1180414openalex-snapshot

Evading network anomaly detection systems

inferredcites →https://doi.org/10.1145/2046684.2046692openalex-snapshot

Adversarial machine learning

inferredcites →https://doi.org/10.1145/2976749.2978392openalex-snapshot

Accessorize to a Crime

inferredcites →https://doi.org/10.4230/oasics.ng-res.2022.1openalex-snapshot

Can We Trust AI-Powered Real-Time Embedded Systems? (Invited Paper)

inferredcites →https://doi.org/10.4230/oasics.saia.2024.1openalex-snapshot

On Assessing ML Model Robustness: A Methodological Framework (Academic Track)

inferredcites →https://doi.org/10.48550/arxiv.1412.5068openalex-snapshot

Towards Deep Neural Network Architectures Robust to Adversarial Examples

inferredcites →https://doi.org/10.48550/arxiv.1705.07204openalex-snapshot

Ensemble Adversarial Training: Attacks and Defenses

inferredcites →https://doi.org/10.48550/arxiv.1712.09665openalex-snapshot

Adversarial Patch

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-10016-0_20openalex-snapshot

Classic Models, Modern Threats: A Study on Adversarial Attack and Defense for Traditional ML Models

inferred← citeshttps://doi.org/10.1007/s11042-024-18563-8openalex-snapshot

Unveiling vulnerabilities: evading YOLOv5 object detection through adversarial perturbations and steganography

inferred← citeshttps://doi.org/10.1007/s13042-025-02862-zopenalex-snapshot

COAA: combined adversarial attacks for deep model vulnerability exploitation

inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109165openalex-snapshot

Time mesh independent framework for learning materials constitutive relationships

inferred← citeshttps://doi.org/10.1038/s41598-025-00890-xopenalex-snapshot

A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing

inferred← citeshttps://doi.org/10.1109/3ict64318.2024.10824286openalex-snapshot

Adversarial Resilience in Image Classification: A Hybrid Approach to Defense

inferred← citeshttps://doi.org/10.1109/access.2024.3487479openalex-snapshot

Evaluating Impact of Image Transformations on Adversarial Examples

inferred← citeshttps://doi.org/10.1109/access.2024.3491017openalex-snapshot

Robustness of Generative Adversarial CLIPs Against Single-Character Adversarial Attacks in Text-to-Image Generation

inferred← citeshttps://doi.org/10.1109/acoit62457.2024.10941671openalex-snapshot

Robust Image Classification: Defensive Strategies against FGSM and PGD Adversarial Attacks

inferred← citeshttps://doi.org/10.1109/icict60155.2024.10544606openalex-snapshot

Fast Gradient Sign Method (FGSM) Variants in White Box Settings: A Comparative Study

inferred← citeshttps://doi.org/10.1109/icscsa66339.2025.11171028openalex-snapshot

QUALICLIPNET: A Hybrid Deep Learning Framework for Robust Image Quality Assessment and Adversarial Resilient Classification

inferred← citeshttps://doi.org/10.1109/ivmsp68335.2026.11618827openalex-snapshot

Threats to Arabic Handwriting Recognition: Investigating Black-Box Adversarial Attacks on Embedded ConvNet Models

inferred← citeshttps://doi.org/10.1109/mic.2024.3450815openalex-snapshot

Measuring AI Fairness in a Continuum Maintaining Nuances: A Robustness Case Study

inferred← citeshttps://doi.org/10.1109/most65065.2025.00041openalex-snapshot

Poster: Adapting Pretrained Vision Transformers with Lora Against Attack Vectors

inferred← citeshttps://doi.org/10.3390/e28020193openalex-snapshot

A Spatially Distributed Perturbation Strategy with Smoothed Gradient Sign Method for Adversarial Analysis of Image Classification Systems

inferred← citeshttps://doi.org/10.3390/math11204272openalex-snapshot

A Comprehensive Review and Analysis of Deep Learning-Based Medical Image Adversarial Attack and Defense

inferred← citeshttps://doi.org/10.3390/rs17020313openalex-snapshot

From Prediction to Explanation: Using Explainable AI to Understand Satellite-Based Riot Forecasting Models

inferred← citeshttps://doi.org/10.7717/peerj-cs.3330openalex-snapshot

Testing the limits: exploring adversarial techniques in AI models

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