Cover Image

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fang, Hao, Qiu, Yixiang, Yu, Hongyao, Yu, Wenbo, Kong, Jiawei, Chong, Baoli, Chen, Bin, Wang, Xuan, Xia, Shu-Tao, Xu, Ke
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
by: Qiu, Yixiang, et al.
Published: (2024)

A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks
by: Qiu, Yixiang, et al.
Published: (2024)

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization
by: Qiu, Yixiang, et al.
Published: (2025)

Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filtering
by: Yu, Hongyao, et al.
Published: (2024)

Enhancing Gradient Inversion Attacks in Federated Learning via Hierarchical Feature Optimization
by: Fang, Hao, et al.
Published: (2026)

GI-NAS: Boosting Gradient Inversion Attacks Through Adaptive Neural Architecture Search
by: Yu, Wenbo, et al.
Published: (2024)

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models
by: Fang, Hao, et al.
Published: (2025)

Revisiting Backdoor Attacks on LLMs: A Stealthy and Practical Poisoning Framework via Harmless Inputs
by: Kong, Jiawei, et al.
Published: (2025)

ICAS: Detecting Training Data from Autoregressive Image Generative Models
by: Yu, Hongyao, et al.
Published: (2025)

CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks
by: Fang, Hao, et al.
Published: (2024)

Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors
by: Fang, Hao, et al.
Published: (2025)

C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts
by: Qing, Chenxi, et al.
Published: (2026)

One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models
by: Fang, Hao, et al.
Published: (2024)

Auditing Privacy in Power Consumption Forecasting: Evaluating Gradient Leakage and Differential Privacy Defenses
by: Rixuan Qiu, et al.
Published: (2025)

Deep Learning Model Inversion Attacks and Defenses: A Comprehensive Survey
by: Yang, Wencheng, et al.
Published: (2025)

The Attack and Defense Landscape of Agentic AI: A Comprehensive Survey
by: Kim, Juhee, et al.
Published: (2026)

Model Inversion Attacks: A Survey of Approaches and Countermeasures
by: Zhou, Zhanke, et al.
Published: (2024)

Maximal $α$-Leakage for Quantum Privacy Mechanisms
by: Yang, Bo-Yu, et al.
Published: (2024)

Neural Antidote: Class-Wise Prompt Tuning for Purifying Backdoors in CLIP
by: Kong, Jiawei, et al.
Published: (2025)

EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
by: Liao, Zeyi, et al.
Published: (2024)

GaussTrap: Stealthy Poisoning Attacks on 3D Gaussian Splatting for Targeted Scene Confusion
by: Hong, Jiaxin, et al.
Published: (2025)

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
by: Chen, Sixu, et al.
Published: (2026)

Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation
by: Yang, Xiaochen, et al.
Published: (2026)

Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs
by: Fang, Hao, et al.
Published: (2025)

Concept-Aware Privacy Mechanisms for Defending Embedding Inversion Attacks
by: Tsai, Yu-Che, et al.
Published: (2026)

Editable-DeepSC: Cross-Modal Editable Semantic Communication Systems
by: Yu, Wenbo, et al.
Published: (2023)

FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses
by: Baglin, Isaac, et al.
Published: (2024)

Attack Anything: Blind DNNs via Universal Background Adversarial Attack
by: Lian, Jiawei, et al.
Published: (2024)

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective
by: Fang, Hao, et al.
Published: (2026)

Learning from the Good Ones: Risk Profiling-Based Defenses Against Evasion Attacks on DNNs
by: Elnawawy, Mohammed, et al.
Published: (2025)

A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations
by: Zhou, Yihe, et al.
Published: (2025)

Seeing Through the Chain: Mitigate Hallucination in Multimodal Reasoning Models via CoT Compression and Contrastive Preference Optimization
by: Fang, Hao, et al.
Published: (2026)

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations
by: Ye, Mang, et al.
Published: (2025)

LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage
by: Nie, Yuzhou, et al.
Published: (2024)

What Your Features Reveal: Data-Efficient Black-Box Feature Inversion Attack for Split DNNs
by: Ren, Zhihan, et al.
Published: (2025)

DNN-Defender: A Victim-Focused In-DRAM Defense Mechanism for Taming Adversarial Weight Attack on DNNs
by: Zhou, Ranyang, et al.
Published: (2023)

H-Mem: A Novel Memory Mechanism for Evolving and Retrieving Agent Memory via a Hybrid Structure
by: Yu, Jiawei, et al.
Published: (2026)

Reasoning Matters: Mitigate Hallucination in Multimodal Large Reasoning Models via Reasoning-Conditioned Preference Optimization
by: Kong, Jiawei, et al.
Published: (2026)

Privacy in Large Language Models: Attacks, Defenses and Future Directions
by: Li, Haoran, et al.
Published: (2023)

Information Leakage of Sentence Embeddings via Generative Embedding Inversion Attacks
by: Tragoudaras, Antonios, et al.
Published: (2025)