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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/AIPAG/SeqMIA

공식 코드

SeqMIA: Sequential-Metric Based Membership Inference Attack

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

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GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation

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

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

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

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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

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

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

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Membership Inference Attacks on Machine Learning: A Survey

https://github.com/MinChen00/UnlearningLeaks

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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-membership-inference-against-generative-networks

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Reconstruction and Membership Inference Attacks against Generative Models

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

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Assessing differentially private deep learning with Membership Inference

https://github.com/aidotse/leakpro

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

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

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Deep Regression Unlearning

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

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Membership Inference Attacks on Lottery Ticket Networks

https://github.com/computationalprivacy/mosaic_memory

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The Mosaic Memory of Large Language Models

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

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Membership Inference Attacks against Machine Learning Models

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

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Membership Inference Attacks against Diffusion Models

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/hyhmia/BlindMI

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Practical Blind Membership Inference Attack via Differential Comparisons

https://github.com/iamgroot42/auditingmi

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Do Parameters Reveal More than Loss for Membership Inference?

https://github.com/iamgroot42/iha_hild

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Do Parameters Reveal More than Loss for Membership Inference?

https://github.com/iamgroot42/mimir

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Do Membership Inference Attacks Work on Large Language Models?

https://github.com/iyempissy/rebMIGraph

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Membership Inference Attack on Graph Neural Networks

https://github.com/izakariyya/idg-dp

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Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity Recognition

https://github.com/jayoungkim408/mia

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An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models

https://github.com/jiangnanh/ppml-workshop

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LTU Attacker for Membership Inference

https://github.com/jiepku/mia-safecompress

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Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment

https://github.com/jiepku/safecompress

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Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment

https://github.com/jinzhuoran/rwku

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RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

https://github.com/khanhnguyen21006/mia_docvqa

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DocMIA: Document-Level Membership Inference Attacks against DocVQA Models

https://github.com/kong13661/pia

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An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization

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