Cover Image

Attack and Defense of Deep Learning Models in the Field of Web Attack Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shi, Lijia, Dong, Shihao
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
by: Zhang, Yiwei, et al.
Published: (2024)

Provable Watermarking for Data Poisoning Attacks
by: Zhu, Yifan, et al.
Published: (2025)

A Taxonomy of Attacks and Defenses in Split Learning
by: Shabbir, Aqsa, et al.
Published: (2025)

SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
by: Paracha, Anum, et al.
Published: (2025)

Synthetic Tabular Data: Methods, Attacks and Defenses
by: Cormode, Graham, et al.
Published: (2025)

Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents
by: Zhan, Qiusi, et al.
Published: (2025)

A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems
by: Tafreshian, Benyamin, et al.
Published: (2025)

A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
by: Purohit, Kiran, et al.
Published: (2023)

Data Reconstruction Attacks and Defenses: A Systematic Evaluation
by: Liu, Sheng, et al.
Published: (2024)

Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
by: Luo, Xinjian, et al.
Published: (2020)

A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)

PECAN: A Deterministic Certified Defense Against Backdoor Attacks
by: Zhang, Yuhao, et al.
Published: (2023)

KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)

Dashed Line Defense: Plug-And-Play Defense Against Adaptive Score-Based Query Attacks
by: Fu, Yanzhang, et al.
Published: (2026)

A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
by: elShehaby, Mohamed, et al.
Published: (2026)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments
by: Zhao, Kaixiang, et al.
Published: (2025)

Sponge Attacks on Sensing AI: Energy-Latency Vulnerabilities and Defense via Model Pruning
by: Hasan, Syed Mhamudul, et al.
Published: (2025)

Learning-based Detection of GPS Spoofing Attack for Quadrotors
by: Wang, Pengyu, et al.
Published: (2025)

In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis
by: Chaudhary, Devashish, et al.
Published: (2026)

Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks
by: Kuo, Kevin, et al.
Published: (2026)

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives
by: Zhao, Kaixiang, et al.
Published: (2025)

Attacks and Defenses Against LLM Fingerprinting
by: Kurian, Kevin, et al.
Published: (2025)

SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
by: Zhang, Heyi, et al.
Published: (2025)

Optimal Attack and Defense for Reinforcement Learning
by: McMahan, Jeremy, et al.
Published: (2023)

Model Hijacking Attack in Federated Learning
by: Li, Zheng, et al.
Published: (2024)

Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies
by: Hayder, Yasmine
Published: (2026)

A Multi-Agent LLM Defense Pipeline Against Prompt Injection Attacks
by: Hossain, S M Asif, et al.
Published: (2025)

Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning
by: Bai, Yuxuan, et al.
Published: (2025)

Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey
by: Truong, Vu Tuan, et al.
Published: (2024)

DiffusionHijack: Supply-Chain PRNG Backdoor Attack on Diffusion Models and Quantum Random Number Defense
by: You, Ziyang, et al.
Published: (2026)

Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
by: Raza, Ali, et al.
Published: (2022)

AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
by: Zeng, Yifan, et al.
Published: (2024)

Optimal Defenses Against Gradient Reconstruction Attacks
by: Chen, Yuxiao, et al.
Published: (2024)

Adversarial Contrastive Learning for LLM Quantization Attacks
by: Song, Dinghong, et al.
Published: (2026)

Test-time Adversarial Defense with Opposite Adversarial Path and High Attack Time Cost
by: Yeh, Cheng-Han, et al.
Published: (2024)

SVDefense: Effective Defense against Gradient Inversion Attacks via Singular Value Decomposition
by: Luo, Chenxiang, et al.
Published: (2025)

Dummy-Aware Weighted Attack (DAWA): Breaking the Safe Sink in Dummy Class Defenses
by: Yu, Yunrui, et al.
Published: (2026)

Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
by: Hong, Hanbin, et al.
Published: (2023)

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
by: Ghosh, Archisman, et al.
Published: (2025)