From 6510af13eb2189c5ba0f70693b23ee6cc2d07f0b Mon Sep 17 00:00:00 2001 From: Naruse Shiroha Date: Tue, 26 Jul 2022 01:21:11 +0800 Subject: [PATCH] update readme --- README.md | 42 +++++++++++++++++++++++++++++++++++++++++- 1 file changed, 41 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index bc98c7a..166fc74 100644 --- a/README.md +++ b/README.md @@ -51,9 +51,28 @@ CVPR 2020 - The Secret Revealer: Generative Model-Inversion Attacks Against Deep APSIPA ASC 2020 - Deep Face Recognizer Privacy Attack: Model Inversion Initialization by a Deep Generative Adversarial Data Space Discriminator. [[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9306253&casa_token=AWugOvIe0I0AAAAA:9wICCkMcfoljMqooM-lgl8m-6F6-cEl-ClHgNkE1SV8mZwqvBIaJ1HDjT1RWLyBz_P7tdB51jQVL&tag=1) -CVPE 2021 - See through gradients: Image batch recovery via gradinversion +CCS 2021 - Membership Leakage in Label-Only Exposures. +[[paper]](https://yangzhangalmo.github.io/papers/CCS21-Label.pdf) +[[code]](https://github.com/zhenglisec/decision-based-mia) + +CCS 2021 - Black-box adversarial attacks on commercial speech platforms with minimal information. +[[paper]](https://dl.acm.org/doi/pdf/10.1145/3460120.3485383) + +CCS 2021 - Unleashing the tiger: Inference attacks on split learning +[[paper]](https://dl.acm.org/doi/pdf/10.1145/3460120.3485259) +[[code]](https://github.com/pasquini-dario/SplitNN_FSHA) + +CVPR 2021 - See through gradients: Image batch recovery via gradinversion. [[paper]](http://openaccess.thecvf.com/content/CVPR2021/papers/Yin_See_Through_Gradients_Image_Batch_Recovery_via_GradInversion_CVPR_2021_paper.pdf) +CVPR 2021 - Soteria: Provable defense against privacy leakage in federated learning from representation perspective. +[[paper]](https://openaccess.thecvf.com/content/CVPR2021/papers/Sun_Soteria_Provable_Defense_Against_Privacy_Leakage_in_Federated_Learning_From_CVPR_2021_paper.pdf) +[[code]](https://github.com/jeremy313/Soteria) + +CVPR 2021 - Imagine: Image synthesis by image-guided model inversion. +[[paper]](https://openaccess.thecvf.com/content/CVPR2021/papers/Wang_IMAGINE_Image_Synthesis_by_Image-Guided_Model_Inversion_CVPR_2021_paper.pdf) + + NeurIPS 2021 - Variational Model Inversion Attacks. [[paper]](https://proceedings.neurips.cc/paper/2021/file/50a074e6a8da4662ae0a29edde722179-Paper.pdf) [[code]](https://github.com/wangkua1/vmi) @@ -68,11 +87,29 @@ ICCV 2021 - Knowledge-Enriched Distributional Model Inversion Attacks. AAAI 2021 - Improving Robustness to Model Inversion Attacks via Mutual Information Regularization. [[paper]](https://arxiv.org/pdf/2009.05241.pdf) +ICML 2021 - Label-Only Membership Inference Attack. +[[paper]](http://proceedings.mlr.press/v139/choquette-choo21a/choquette-choo21a.pdf) +[[code]](https://github.com/cchoquette/membership-inference) + +ICML 2021 - When Does Data Augmentation Help With Membership Inference Attacks? +[[paper]](When Does Data Augmentation Help With Membership Inference Attacks?) + ICLR 2021 workshop - PRACTICAL DEFENCES AGAINST MODEL INVERSION ATTACKS FOR SPLIT NEURAL NETWORKS. [[paper]](https://arxiv.org/pdf/2104.05743.pdf) [[code]](https://github.com/TTitcombe/Model-Inversion-SplitNN) [[video]](https://crossminds.ai/video/practical-defences-against-model-inversion-attacks-for-split-neural-networks-60c3cee46af07cfaf7325850/) +ICDE 2021 Feature inference attack on model predictions in vertical federated learning. +[[paper]](https://arxiv.org/pdf/2010.10152) +[[code]](https://github.com/xj231/featureinference-vfl) + +DAC 2021 - PRID: Model Inversion Privacy Attacks in Hyperdimensional Learning Systems +[[paper]](https://dl.acm.org/doi/abs/10.1109/DAC18074.2021.9586217) + +ICSE 2021 - Robustness of on-device models: Adversarial attack to deep learning models on android apps. +[[paper]](https://arxiv.org/pdf/2101.04401) +[[code]] + ICML 2022 - Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks. [[paper]](https://arxiv.org/pdf/2201.12179.pdf) [[code]](https://github.com/LukasStruppek/Plug-and-Play-Attacks) @@ -93,6 +130,9 @@ IEEE 2022 - An Approximate Memory based Defense against Model Inversion Attacks [[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9792582&casa_token=ymT57RhNhGEAAAAA:WsQHMpv77-4uyIp7l-p4hc7_Qmxvn5TeNpS5F7LHBFHyLay2O8Pe5eWqsKN2fu56v98NZsRrqeit) [[code]](https://github.com/katekemu/model_inversion_defense) +TIFS 2022 - Model Inversion Attack by Integration of Deep Generative Models: Privacy-Sensitive Face Generation From a Face Recognition System +[[paper]](https://dl.acm.org/doi/abs/10.1109/TIFS.2022.3140687) + ### Graph learning domain