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Membership Inference Attack

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코드

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

https://github.com/liar-mask/fedmia

공식 코드

FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning

https://github.com/lions-epfl/vl-mia

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Membership Inference Attacks against Large Vision-Language Models

https://github.com/lioutang/unlearn-apollo-attack

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Apollo: A Posteriori Label-Only Membership Inference Attack Towards Machine Unlearning

https://github.com/liuyugeng/ml-doctor

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ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models

https://github.com/luckyos-code/mia-covid

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Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)

https://github.com/machine-learning-security-lab/mia_prune

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Membership Inference Attacks and Defenses in Neural Network Pruning

https://github.com/meghdad92/scrub

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Towards Unbounded Machine Unlearning

https://github.com/microsoft/intrinsic-private-sgd

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An Empirical Study on the Intrinsic Privacy of SGD

https://github.com/minxingzhang/miagm

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Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models

https://github.com/multimodalmi/multimodal-membership-inference

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M^4I: Multi-modal Models Membership Inference

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

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

https://github.com/ocram17/duck

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DUCK: Distance-based Unlearning via Centroid Kinematics

https://github.com/privacytrustlab/ml_privacy_meter

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ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning

https://github.com/s3l-official/slmia-sr

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SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems

https://github.com/salehzz/acmia

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Automatic Calibration for Membership Inference Attack on Large Language Models

https://github.com/shrezaei/MI-on-EL

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Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective

https://github.com/soumyaxyz/Privacy-Preserving-Federated-Learning

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MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated Learning

https://github.com/spin-umass/membershipwhiteboxattacks

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Efficient passive membership inference attack in federated learning

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

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Disparate Vulnerability to Membership Inference Attacks

https://github.com/sprintml/privacy_attacks_against_iars

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Privacy Attacks on Image AutoRegressive Models

https://github.com/t3humphries/non-iid-mia

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Investigating Membership Inference Attacks under Data Dependencies

https://github.com/tanjasper/parameters_or_privacy

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Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference

https://github.com/tleemann/gaussian_mip

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Gaussian Membership Inference Privacy

https://github.com/trucndt/ami

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Active Membership Inference Attack under Local Differential Privacy in Federated Learning

https://github.com/trustworthygnn/mia-gnn

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Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications

https://github.com/tsinghua-fib-lab/neurips2024_spv-mia

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Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

https://github.com/ukplab/iclr2025-psa

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Differentially Private Steering for Large Language Model Alignment

https://github.com/um-dsp/DP-UTIL

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DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine Learning

https://github.com/um-dsp/PRICURE

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PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party Setting

https://github.com/vita-group/shake-to-leak

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Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk

https://github.com/wjfu99/MIA-LLMs

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Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

https://github.com/wjfu99/mia-gen

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A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models

https://github.com/wjfu99/mia-tuner

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MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector

https://github.com/xinleihe/semi-leak

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Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning

https://github.com/yukehu/vlm_mia

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Membership Inference Attacks Against Vision-Language Models

https://github.com/yyy01/pac

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Data Contamination Calibration for Black-box LLMs

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