From 8fbfbd76d8b34df633daa13eca24c8dc5f54b2ce Mon Sep 17 00:00:00 2001 From: AndrewZhou924 Date: Sat, 15 Jul 2023 15:18:57 +0800 Subject: [PATCH] delete --- README.md | 28 ++++------------------------ 1 file changed, 4 insertions(+), 24 deletions(-) diff --git a/README.md b/README.md index 739475e..be549ee 100644 --- a/README.md +++ b/README.md @@ -5,16 +5,17 @@ Stars

A curated list of resources for model inversion attack (MIA). -If some related papers are missing, please contact us via pull requests. + +If some related papers are missing, please contact us via pull requests :) **Outlines:** + - [What is the model inversion attack?](#what-is-the-model-inversion-attack) - [Survey](#survey) - [Computer vision domain](#computer-vision-domain) - [TODO](#todo) - [Graph learning domain](#graph-learning-domain) - - [TODO](#todo-1) - [Natural language processing domain](#natural-language-processing-domain) - [Tools](#tools) - [Others](#others) @@ -474,28 +475,7 @@ CVPR 2023 - Re-thinking Model Inversion Attacks Against Deep Neural Networks | 2022 | Finding MNEMON: Reviving Memories of Node Embeddings | - | CCS | [Paper](https://arxiv.org/pdf/2204.06963.pdf) | - | | 2022 | Defense against membership inference attack in graph neural networks through graph perturbation | - | IJIS | [Paper](https://link.springer.com/article/10.1007/s10207-022-00646-y) | - | | 2022 | Model Inversion Attacks against Graph Neural Networks | - | TKDE | [Paper](https://arxiv.org/pdf/2209.07807.pdf) | - | -| 2023 | On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation | - | ICML | -[Paper](https://openreview.net/pdf?id=Vcl3qckVyh) | [Code](https://github.com/tmlr-group/MC-GRA) | - -### TODO -| Year | Title | Venue | Paper Link | Code Link | -| ---- | ----- | ----- | ---------- | --------- | -| 2021 | Membership Inference Attack on Graph Neural Networks | International Conference on Trust, Privacy and Security in Intelligent Systems and Applications | [Paper](https://arxiv.org/pdf/2101.06570.pdf) | - | -| 2020 | Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realisation | ACM Asia Conference on Computer and Communications Security | [Paper](https://arxiv.org/pdf/2010.12751.pdf) | - | -| 2021 | Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications | Industrial Conference on Data Mining | [Paper](https://arxiv.org/pdf/2110.08760.pdf) | - | -| 2020 | Locally Private Graph Neural Networks | Conference on Computer and Communications Security | [Paper](https://arxiv.org/pdf/2006.05535.pdf) | - | -| 2020 | Backdoor Attacks to Graph Neural Networks | ACM Symposium on Access Control Models and Technologies | [Paper](https://arxiv.org/pdf/2006.11165.pdf) | - | -| 2019 | Attacking Graph-based Classification via Manipulating the Graph Structure | Conference on Computer and Communications Security | [Paper](https://arxiv.org/pdf/1903.00553.pdf) | - | -| 2021 | Private Graph Data Release: A Survey | ACM Computing Surveys | [Paper](https://arxiv.org/pdf/2107.04245.pdf) | -| 2022 | Differentially Private Graph Neural Networks for Whole-Graph Classification | IEEE Transactions on Pattern Analysis and Machine Intelligence | [Paper](https://ieeexplore.ieee.org/ielx7/34/4359286/09980390.pdf) | - | -| ---- | Node-Differentially Private Estimation of the Number of Connected Components | arXiv | [Paper](https://arxiv.org/pdf/2304.05890.pdf) | - | -| 2022 | LPGNet: Link Private Graph Networks for Node Classification | Conference on Computer and Communications Security | [Paper](https://arxiv.org/pdf/2205.03105.pdf) | - | -| ---- | Releasing Graph Neural Networks with Differential Privacy Guarantees | arXiv | [Paper](https://arxiv.org/pdf/2109.08907.pdf) | - | -| 2021 | DPGraph: A Benchmark Platform for Differentially Private Graph Analysis | SIGMOD Conference | [Paper](https://dl.acm.org/doi/pdf/10.1145/3448016.3452756) | - | -| 2015 | Private Release of Graph Statistics using Ladder Functions | SIGMOD Conference | [Paper](http://wrap.warwick.ac.uk/67368/7/WRAP_Cormode.pdf) | - | -| 2021 | LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis | IEEE Symposium on Security and Privacy | [Paper](https://arxiv.org/pdf/2108.06504.pdf) | - | -| ---- | GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation | arXiv | [Paper](https://arxiv.org/pdf/2203.00949.pdf) | - | -| ---- | GrOVe: Ownership Verification of Graph Neural Networks using Embeddings | arXiv | [Paper](https://arxiv.org/pdf/2304.08566.pdf) | - | +| 2023 | On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation | white-box | ICML |[Paper](https://openreview.net/pdf?id=Vcl3qckVyh) | [Code](https://github.com/tmlr-group/MC-GRA) |