Quick Links (this page):

• Source Attack Libraries
• Research Codebases
• Other Resources
• Membership Inference
• Gradient attacks

Open Source Attack Libraries:

• Membership Inference (Black Box) (DT, NN)
• Attribute Inference (Black Box) (DT, NN)
• Attribute Inference (white box) (scikit DT)
• Model Inversion (White Box) (NN)
• Row Reconstruction (White Box) (DT, NN)
• Other Attacks
• Supported Estimators Not all estimators work with all attacks.

• Membership Inference (Black Box) (NN) [Metrics Module]
• Supported Estimators These can be extended easily to support other estimators.
• Reference MI attacks

• Membership Inference (Black Box) (NN) [(All membership attacks)
• Secret Sharer Attack (White Box) (NN)

• Attacks

Research Codebases:

• Membership Inference (Black Box) (NN)
• Attribute InferenceSecret Sharer Attack (Black Box And White Box) (NN)

• Paper
• Membership Inference (Black Box) (NN)

• Supported algorithms

• Evasion and Poisoning attacks only

• Membership inference in federated learning settings

• Data reconstruction using gradient
• Examples

• Data reconstruction using gradients

Other Resources:

• Membership Inference Attacks and Defenses on Machine Learning Models Literature
• Membership Inference Competition MICO Microsoft
• Awesome ML Privacy Attacks (has code links)
• Survey ML Attacks paper
• Membership attacks on tradition models
• Feature Inference Attack on Model Predictions in Vertical Federated Learning,
• Privacy Preserving Machine Learning Resources
• Overview of Fed Deep Learning Privacy Attacks and Defensive Strategies
• PrivacyFL: A simulator for privacy-preserving and secure federated learning
• Client Privacy Leakage attacks in FL
• Fairness and Privacy-Preserving in Federated Learning: A Survey
• Inverting Gradient in FL
• Unleashing the Tiger: Inference Attacks on Split Learning
• From Gradient Leakage to Adversarial Attacks in Federated Learning
• Presentation: Privacy attacks on Decision Trees
• Membership Inference Attacks on Federated Horizontal Gradient Boosted Decision Trees
• https://dl.acm.org/doi/full/10.1145/3624010

Membership Inference:

• Membership Inference Attacks Against Machine Learning Models
• Evaluating Membership Inference Attacks and Defenses in Federated Learning

Gradient Attacks:

• Inverting Gradients - How easy is it to break privacy in federated learning?