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ML_privacy_links

General Privacy Links:

https://absorbed-gourd-1ac.notion.site/Privacy-AI-4285bcd61c9d48c980c329be62fe204a

https://ssgit.skku.edu/hojoon.lee/sslab-training-program

https://github.com/stratosphereips/awesome-ml-privacy-attacks

https://github.com/Koukyosyumei/Attack_SplitNN

https://github.com/SAP-samples/machine-learning-diff-private-federated-learning

https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning

https://github.com/Koukyosyumei/AIJack

https://github.com/tensorflow/privacy/tree/master/research

https://github.com/stratosphereips/awesome-ml-privacy-attacks#privacy-testing-tools

https://github.com/orgs/DPBayes/repositories

Model Stealing Attack:

https://github.com/ftramer/Steal-ML

Membership Inference Attack:

For membership inference attack, decomposing output probability vector can be of great importance:

https://github.com/kundajelab/deeplift#do-you-have-support-for-non-keras-models

https://notebook.community/tensorflow/privacy/tensorflow_privacy/privacy/membership_inference_attack/codelab

https://github.com/tensorflow/privacy/tree/master/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack

https://github.com/tensorflow/privacy/tree/master/tensorflow_privacy/privacy/privacy_tests/membership_inference_attack/codelabs

https://github.com/spring-epfl/mia

https://github.com/PrivPkt/PrivPkt

https://github.com/MinghuiChen43/awesome-trustworthy-deep-learning

https://github.com/liuyugeng/ML-Doctor

https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning

https://github.com/shilab/DP-MIA

https://pypi.org/project/mia/

https://github.com/csong27/membership-inference

https://github.com/yigitcankaya/augmentation_mia

https://github.com/yonsei-cysec/Membership_Inference_Attack

https://github.com/ml-research/To-Trust-or-Not-To-Trust-Prediction-Scores-for-Membership-Inference-Attacks

https://github.com/HongshengHu/membership-inference-machine-learning-literature

https://github.com/BielStela/membership_inference

https://github.com/inspire-group/membership-inference-evaluation

https://github.com/tensorflow/privacy

https://github.com/BielStela/membership_inference

https://github.com/AdrienBenamira/membership_inference_attack

https://github.com/cchoquette/membership-inference

https://github.com/microsoft/privGAN

https://github.com/MultimodalMI/Multimodal-membership-inference

https://github.com/DingfanChen/GAN-Leaks

https://github.com/AhmedSalem2/ML-Leaks

https://github.com/jhayes14/gen_mem_inf

https://github.com/MultimodalMI/Multimodal-membership-inference

https://github.com/TrustworthyGNN/MIA-GNN

https://github.com/TrustworthyGNN/MIA-GNN

https://github.com/abogdanova/FL-MIA

https://github.com/yonsei-cysec/Membership_Inference_Attack

https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning

https://github.com/pg1647/IntromlProject

https://github.com/DingfanChen/RelaxLoss

https://github.com/SAP-samples/security-research-membership-inference-and-differential-privacy

https://github.com/Jongho0/ml_mbr_inf

https://github.com/SSAW14/segmentation_membership_inference

https://github.com/gongzhimin/Membership-Inference-Attack-in-Federated-Learning

https://github.com/RayTzeng/s3m-membership-inference

https://github.com/spring-epfl/disparate-vulnerability

https://github.com/icmpnorequest/MLSec

https://github.com/HongshengHu/membership-inference-via-backdooring

https://github.com/sharmi1206/Membership_Inference_Attack_DP

https://github.com/yechanp/Membership-Inference-Attacks-Against-Object-Detection-Models

https://github.com/work-hard-play-harder/PAR-GAN

https://github.com/facebookresearch/calibration_membership

https://github.com/Machine-Learning-Security-Lab/mia_prune

https://github.com/sharmi1206/Membership_Inference_Attack_DP

https://github.com/facebookresearch/whitebox_blackbox

https://github.com/SAP-archive/security-research-membership-inference-against-generative-networks

https://github.com/Tidistamatiou/Differential_privacy_membership_inference_attack

https://github.com/knightcao/MembershipPrivacy

https://github.com/MIA-FL/SP22

https://github.com/RemiBERNHARD/Membership_Inference_Attacks

https://github.com/microsoft/responsible-ai-toolbox-privacy

https://github.com/sorami/TACL-Membership

https://github.com/Zhouzp2115/MembershipInference

https://github.com/erfanhss/MembershipInference

https://github.com/yigitcankaya/augmentation_mia

https://github.com/yigitcankaya/augmentation_mia

https://github.com/cardwizard/membershipInferenceLottery

https://github.com/codeLAlit/MembershipInferenceAttack_ML

https://github.com/navodas/MIA

https://github.com/xingzix/Membership_Inference

https://github.com/Rashid-Ahmed/Membership-Inference

https://github.com/revbucket/membership_inference

https://github.com/soumik9876/membership-inference

https://github.com/McBoar/membership_inference

https://github.com/Pierreoo/Membership-Inference

https://github.com/MhmudFwzi/attacking-ML-models-privacy

https://github.com/ml-research/To-Trust-or-Not-To-Trust-Prediction-Scores-for-Membership-Inference-Attacks

https://github.com/seclab-yonsei/mia-ko-lm

https://github.com/chnyangs/membership-inference-attacks

https://www.catalyzex.com/s/Inference%20Attack

https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning

https://github.com/HongshengHu/membership-inference-machine-learning-literature

https://github.com/BielStela/membership_inference

https://github.com/RayTzeng/s3m-membership-inference

https://franziska-boenisch.de/posts/2021/01/membership-inference/

https://github.com/csong27/membership-inference

https://github.com/spring-epfl/mia

https://github.com/spring-epfl/mia

https://www.tensorflow.org/responsible_ai/privacy/tutorials/privacy_report

https://pages.nist.gov/dioptra/tutorials/example-pytorch-mnist-membership-inference.html

https://github.com/avitalsh/reconst_based_MIA

https://github.com/sorami/tacl-membership

https://people.duke.edu/~zg70/dataset.html

https://github.com/yigitcankaya/augmentation_mia

https://www.mindspore.cn/mindarmour/docs/en/master/test_model_security_membership_inference.html

https://github.com/HongshengHu/membership-inference-via-backdooring

https://github.com/DingfanChen/RelaxLoss

https://www.github.com/stanleykywu/model-updates

https://gab41.lab41.org/membership-inference-attacks-on-neural-networks-c9dee3db67da

https://github.com/privacytrustlab/ml_privacy_meter

https://techairesearch.com/inference-attacks-against-machine-learning-models/

https://github.com/Lab41/cyphercat

https://github.com/RayTzeng/s3m-membership-inference

https://github.com/AhmedSalem2/ML-Leaks

https://github.com/pytorch/opacus

https://github.com/privacytrustlab/ml_privacy_meter/tree/master/docs

Adversarial Attack

https://github.com/Lab41/cyphercat

https://github.com/chnyangs/membership-inference-attacks

https://github.com/Gayatri-Priyadarsini/Membership-inference-attack

https://github.com/donakq/MSE-234-Membership_Inference

https://github.com/tylershumaker/membership-inference-vulnerability

https://github.com/chiragdaryani/membership-inference-attack-NN

https://github.com/AdamWei-boop/Membership-Inference-Attack-NN

https://github.com/peddinti95/Membership_Inference_Attack

https://github.com/AdamWei-boop/Membership-Inference-Attack-LGBM

https://github.com/JJublanc/membership_inference_attacks

https://github.com/hu-tianyi/Membership_Inference_Attack

https://github.com/aischeveva/dp_classifier_membership_inference

https://github.com/diybu/Haplotype-based-membership-inferences

https://github.com/ShamimurRahmanShuvo/Membership-Inference-Attacks-Mitigation

https://github.com/KK-Gayatri-P/Membership-Inference-Attacks

https://github.com/ErwinSCat/set_membership_inference

https://github.com/DisaitekAI/membership_inference_attack

https://github.com/anonymus369/Formalizing-Attribute-and-Membership-Inference

https://github.com/avitalsh/reconst_based_MIA

https://github.com/elisim/Membership-Code

https://github.com/thedionysus/pse_in_ml_ex3_membership_inference

https://github.com/plll4zzx/Evaluating-Membership-Inference-Through-Adversarial-Robustness

https://github.com/saeid651/MMSBM-VI

https://github.com/ablancoj/dp-mia

https://github.com/thedionysus/pse_in_ml_ex3_membership_inference

https://github.com/plll4zzx/Evaluating-Membership-Inference-Through-Adversarial-Robustness

https://github.com/ablancoj/dp-mia

https://github.com/L1n111ya/MIA_project

https://github.com/saeid651/MMSBM-VI

https://github.com/anony-submission/MIA_evaluation

https://github.com/vasishtduddu/MIADatasets

https://github.com/Noilyn/miatesting

https://github.com/ranasalalali/spacy_mi

https://github.com/giladcohen/sif_mi_attack

https://github.com/duoergun0729/MIAA

https://github.com/nervjack2/Membership-Inference-Attack-on-zh-en-NLP-Translation-Model

https://github.com/skyInGitHub/The-Audio-Auditor

https://github.com/hallojs/nn_direct_mia

https://github.com/nsusarla-eng/COMP90055-Code

https://github.com/nsusarla-eng/COMP90055-Code

https://github.com/L1n111ya/SL-MIA

https://github.com/aks2203/poisoning-benchmark

https://github.com/as791/Adversarial-Example-Attack-and-Defense/blob/master/Adversarial_Example_(Attack_and_defense).ipynb

https://github.com/fursovia/dilma

https://github.com/fursovia/dilma

Unintended Memorization:

https://github.com/MinChen00/UnlearningLeaks

Reidentification risk:

https://github.com/d-o-m-i-n-i-k/re-identification-risk

https://cloud.google.com/dlp/docs/concepts-risk-analysis

Membership Filter

https://github.com/FastFilter/fastfilter_java

https://github.com/FastFilter/fastfilter_cpp

https://github.com/maziarg/PrivAttack-BCQ

https://github.com/ctom2/seg-mia

https://github.com/nreje/PrivacyResults

https://github.com/TinfoilHat0/MemberInference-by-LossThreshold

https://github.com/brij1823/CMPUT-664-Membership-Inference-Attacks-Against-Supervised-Learning-Models-on-Textual-Data

https://github.com/dzhong2/MIA_disparity

https://github.com/ale-gaudenzi/tfpmia

https://github.com/iaescala/m31-bayes

https://github.com/TinfoilHat0/RelaxLoss

https://github.com/lzbuuu/MIAoMU

https://github.com/OliverRoss/replicating_mia

https://github.com/stanleykywu/model-updates

https://github.com/SJabin/Data_Model_Dependencies_MIA

https://github.com/mejbahshameem/privacy-enhancing-technologies

https://github.com/aneezJaheez/MIA

https://github.com/snpushpi/Differential-Privacy-in-Split-Learning

https://github.com/SAP-samples/security-research-fed-dp-mia

https://github.com/ganeshdg95/Privacy-and-Performance-in-Power-Consumption-Curve-Generation-with-GANs

https://github.com/e0336110/notebooks

Model Inversion Attack:

https://openreview.net/forum?id=6iqd9JAVR1z

https://github.com/DistributedML/FoolsGold

By performing model extraction attack, may be one can construct training data from its gradients...as the original paper is designed from federated learning with immature gradients...which may be isomorphic to

https://github.com/Koukyosyumei/AIJack

https://github.com/yashkant/Model-Inversion-Attack

https://github.com/liuyugeng/ML-Doctor

https://github.com/Koukyosyumei/Attack_SplitNN

https://github.com/zhangzp9970/MIA

https://github.com/AndrewZhou924/Awesome-model-inversion-attack

https://github.com/TTitcombe/Model-Inversion-SplitNN

https://github.com/xpeng9719/Defend_MI

https://github.com/qwqoro/ML-Talk

https://github.com/katekemu/model_inversion_defense

https://github.com/zhangzp9970/TB-MIA

https://github.com/wangkua1/vmi

https://github.com/SCccc21/Knowledge-Enriched-DMI

https://github.com/scccc21/knowledge-enriched-dmi

https://blog.openmined.org/tag/privacy-attack/

https://franziska-boenisch.de/posts/2020/12/model-inversion/

https://github.com/m-kahla/Label-Only-Model-Inversion-Attacks-via-Boundary-Repulsion

https://blog.trailofbits.com/2020/10/08/privacyraven-has-left-the-nest/

https://github.com/trailofbits/PrivacyRaven

https://github.com/LukasStruppek/Plug-and-Play-Attacks

https://github.com/JJublanc/model_inversion_attack

https://github.com/smehnaz/black-boxMIAI

https://github.com/smehnaz/black-boxMIAI

https://github.com/ruoxi-jia-group

https://github.com/zlijingtao/ResSFL

https://www.catalyzex.com/s/Inference%20Attack

https://notebook.community/OpenMined/PySyft/examples/tutorials/advanced/privacy_attacks/Tutorial%201%20-%20Black%20box%20model%20inversion

https://github.com/zechenghe/Inverse_Collaborative_Inference

https://github.com/zechenghe/Inverse_Collaborative_Inference

https://pytorch.org/tutorials/beginner/fgsm_tutorial.html

https://github.com/OpenMined/PySyft

https://towardsdatascience.com/differential-privacy-in-deep-learning-cf9cc3591d28

https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning

https://github.com/sarahsimionescu/simple-model-inversion

https://github.com/katekemu/model_inversion_defense

https://github.com/Pilladian/ml-attack-framework

https://github.com/pytorch/opacus

https://github.com/Trusted-AI/adversarial-robustness-toolbox

https://franziska-boenisch.de/posts/2020/12/model-inversion/

https://github.com/IBM/ai-privacy-toolkit

https://github.com/IBM/differential-privacy-library

Compiler

https://github.com/tf-encrypted/tf-encrypted

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