The code for prior GLA works

The code for prior works

1. iDLG: Improved Deep Leakage from Gradients
   • paper: https://arxiv.org/pdf/2001.02610.pdf
   • code: PatrickZH/Improved-Deep-Leakage-from-Gradients: The code for “Improved Deep Leakage from Gradients” (iDLG). (github.com)
2. Inverting Gradients - How easy is it to break privacy in federated learning?
   • paper: https://arxiv.org/abs/2003.14053
   • code: JonasGeiping/invertinggradients: Algorithms to recover input data from their gradient signal through a neural network (github.com)
3. Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage
   • paper: https://arxiv.org/pdf/2203.15696.pdf
   • code: zhuohangli/GGL: A pytorch implementation of the paper “Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage”. (github.com)
4. Exploiting Unintended Feature Leakage in Collaborative Learning
   • paper: https://arxiv.org/pdf/1805.04049.pdf
   • code: csong27/property-inference-collaborative-ml: Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019) (github.com)
5. Fast Generation-Based Gradient Leakage Attacks against Highly Compressed Gradients
   • paper:
   • code: pigeon-dove/FGLA: FGLA: Fast Generation-Based Gradient Leakage Attacks against Highly Compressed Gradients (github.com)
6. Gradient Inversion with Generative Image Prior
   • paper: https://arxiv.org/abs/2110.14962
   • code: https://github.com/ml-postech/gradient-inversion-generative-image-prior
7. Gradient Obfuscation Gives a False Sense of Security in Federated Learning
   • paper: [2206.04055] Gradient Obfuscation Gives a False Sense of Security in Federated Learning (arxiv.org)
   • code: https://github.com/KAI-YUE/rog
8. GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning
   • paper: http://arxiv.org/abs/2105.00529
   • code: https://github.com/Rand2AI/GRNN
9. LAMP: Extracting Text from Gradients with Language Model Priors
   • paper: [2202.08827] LAMP: Extracting Text from Gradients with Language Model Priors (arxiv.org)
   • code: eth-sri/lamp: LAMP: Extracting Text from Gradients with Language Model Priors (NeurIPS '22) (github.com)
10. R-GAP: RECURSIVE GRADIENT ATTACK ON PRIVACY
    • paper: [2010.07733] R-GAP: Recursive Gradient Attack on Privacy (arxiv.org)
    • code: JunyiZhu-AI/R-GAP: Recursive Gradient Attack on Privacy (github.com)
11. ROBBING THE FED: DIRECTLY OBTAINING PRIVATE DATA IN FEDERATED LEARNING WITH MODIFIED MODELS
    • paper: [2110.13057] Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models (arxiv.org)
    • code: lhfowl/robbing_the_fed (github.com)
12. User-Level Label Leakage from Gradients in Federated Learning
    • paper: [2105.09369] User-Level Label Leakage from Gradients in Federated Learning (arxiv.org)
    • code: tklab-tud/LLG (github.com)