Cover Image

Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filtering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yu, Hongyao, Qiu, Yixiang, Fang, Hao, Zhuang, Tianqu, Chen, Bin, Yu, Sijin, Wang, Bin, Xia, Shu-Tao, Xu, Ke
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Computer Vision and Pattern Recognition Machine Learning
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)

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

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

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

Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks
by: Kang, Tianqu, et al.
Published: (2024)

Defending Against Neural Network Model Inversion Attacks via Data Poisoning
by: Zhou, Shuai, et al.
Published: (2024)

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

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

Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)

Poisoning Attacks to Local Differential Privacy for Ranking Estimation
by: Zhan, Pei, et al.
Published: (2025)

Defending Against Prompt Injection with DataFilter
by: Wang, Yizhu, et al.
Published: (2025)

Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-based LLM Systems
by: Dong, Yueyan, et al.
Published: (2026)

TextCrafter: Optimization-Calibrated Noise for Defending Against Text Embedding Inversion
by: Tang, Duoxun, et al.
Published: (2025)

SEAL: Entangled White-box Watermarks on Low-Rank Adaptation
by: Oh, Giyeong, et al.
Published: (2025)

Low Rank Adaptation for Adversarial Perturbation
by: Liu, Han, et al.
Published: (2026)

Secure and Scalable Face Retrieval via Cancelable Product Quantization
by: Tang, Haomiao, et al.
Published: (2025)

Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
by: Wang, Yujing, et al.
Published: (2024)

JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation
by: Zhang, Shenyi, et al.
Published: (2025)

HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
by: Qiu, Pengyu, et al.
Published: (2022)

Eguard: Defending LLM Embeddings Against Inversion Attacks via Text Mutual Information Optimization
by: Liu, Tiantian, et al.
Published: (2024)

HSF: Defending against Jailbreak Attacks with Hidden State Filtering
by: Qian, Cheng, et al.
Published: (2024)

Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning
by: Liu, Xiao-Yang, et al.
Published: (2023)

Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks
by: Xue, Lulu, et al.
Published: (2024)

Defending against Data Poisoning Attacks in Federated Learning via User Elimination
by: Galanis, Nick
Published: (2024)

Why does weak-OOD help? A Further Step Towards Understanding Jailbreaking VLMs
by: Zhou, Yuxuan, et al.
Published: (2025)

Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs
by: Liu, Fan, et al.
Published: (2024)

WATER-GS: Toward Copyright Protection for 3D Gaussian Splatting via Universal Watermarking
by: Tan, Yuqi, et al.
Published: (2024)

Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
by: Liu, Yu-An, et al.
Published: (2024)

Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss
by: Yang, Guang, et al.
Published: (2024)

Attention is All You Need to Defend Against Indirect Prompt Injection Attacks in LLMs
by: Zhong, Yinan, et al.
Published: (2025)

Robustness via Referencing: Defending against Prompt Injection Attacks by Referencing the Executed Instruction
by: Chen, Yulin, et al.
Published: (2025)

Defending Against Attack on the Cloned: In-Band Active Man-in-the-Middle Detection for the Signal Protocol
by: Teng, Wil Liam, et al.
Published: (2024)

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
by: Peng, Wanli, et al.
Published: (2025)

Rate-Optimal Rank Aggregation with Private Pairwise Rankings
by: Xu, Shirong, et al.
Published: (2024)

CodePurify: Defend Backdoor Attacks on Neural Code Models via Entropy-based Purification
by: Mu, Fangwen, et al.
Published: (2024)

FL-Defender: Combating Targeted Attacks in Federated Learning
by: Jebreel, Najeeb, et al.
Published: (2022)

Invariant Aggregator for Defending against Federated Backdoor Attacks
by: Wang, Xiaoyang, et al.
Published: (2022)

Beyond a Single Perspective: Towards a Realistic Evaluation of Website Fingerprinting Attacks
by: Deng, Xinhao, et al.
Published: (2025)

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

Cryptographic Application of Elliptic Curve with High Rank
by: Cheng, Xiaogang, et al.
Published: (2025)