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Inference Attack

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AIPAG/SeqMIA

공식 코드

SeqMIA: Sequential-Metric Based Membership Inference Attack

https://github.com/AIRI-Institute/GLiRA

공식 코드

GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation

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

공식 코드

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

https://github.com/Brophy-E/ECG_GAN_MBD

공식 코드

Synthesis of Realistic ECG using Generative Adversarial Networks

https://github.com/DependableSystemsLab/code_poison_MIA

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A Method to Facilitate Membership Inference Attacks in Deep Learning Models

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

공식 코드

GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models

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

공식 코드

Membership Inference Attacks on Machine Learning: A Survey

https://github.com/MinChen00/UnlearningLeaks

공식 코드

When Machine Unlearning Jeopardizes Privacy

https://github.com/SAP-samples/security-research-dp-hierarchical-text

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On the privacy-utility trade-off in differentially private hierarchical text classification

https://github.com/SAP-samples/security-research-identifiability-in-dpdl

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Quantifying identifiability to choose and audit $ε$ in differentially private deep learning

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

공식 코드

Reconstruction and Membership Inference Attacks against Generative Models

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

공식 코드

Assessing differentially private deep learning with Membership Inference

https://github.com/Zhou-Junhao/PIA_GAN

공식 코드

Property Inference Attacks Against GANs

https://github.com/aidotse/leakpro

공식 코드

Technical Report for the Forgotten-by-Design Project: Targeted Obfuscation for Machine Learning

https://github.com/ayu987/deep-regression-unlearning

공식 코드

Deep Regression Unlearning

https://github.com/bargavj/EvaluatingDPML

공식 코드

Revisiting Membership Inference Under Realistic Assumptions

https://github.com/bridgesra/expm_nf_mimic3_results_code

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Are Normalizing Flows the Key to Unlocking the Exponential Mechanism?

https://github.com/cardwizard/membershipInferenceLottery

공식 코드

Membership Inference Attacks on Lottery Ticket Networks

https://github.com/computationalprivacy/ml-correlation-inference

공식 코드

Correlation inference attacks against machine learning models

https://github.com/computationalprivacy/mosaic_memory

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The Mosaic Memory of Large Language Models

https://github.com/cp-lab-uts/reinforcement-unlearning

공식 코드

Reinforcement Unlearning

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

공식 코드

Membership Inference Attacks against Machine Learning Models

https://github.com/d0mih/clipping_privacy

공식 코드

Does CLIP Know My Face?

https://github.com/d0mih/does-clip-know-my-face

공식 코드

Does CLIP Know My Face?

https://github.com/datasec-lab/ruli

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Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective

https://github.com/ellisalicante/ma-fl-mia

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Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated Learning

https://github.com/friedronaldo/primitives-ps

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Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data

https://github.com/fseclab-osaka/mia-diffusion

공식 코드

Membership Inference Attacks against Diffusion Models

https://github.com/fumiyukikato/fl-tee

공식 코드

OLIVE: Oblivious Federated Learning on Trusted Execution Environment against the risk of sparsification

https://github.com/g-pichler/dishonest_mia

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Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning

https://github.com/giladcohen/sif_mi_attack

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Membership Inference Attack Using Self Influence Functions

https://github.com/hassanalikhatim/amia

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Membership Inference Attacks on DNNs using Adversarial Perturbations

https://github.com/hkust-knowcomp/uc-fedrec

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User Consented Federated Recommender System Against Personalized Attribute Inference Attack

https://github.com/hongshenghu/source-inference-fl

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Source Inference Attacks in Federated Learning

https://github.com/hyhmia/BlindMI

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Practical Blind Membership Inference Attack via Differential Comparisons

https://github.com/iamgroot42/auditingmi

공식 코드

Do Parameters Reveal More than Loss for Membership Inference?

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