This page provides the attacks and factors that have a negative impact “Reconstruction of training data” in the information systems aspect in the AI Security Map, the defense methods and countermeasures against them, as well as the relevant AI technologies, tasks, and data. It also indicates related elements in the external influence aspect.
Attack or cause
- Model inversion
Defensive method or countermeasure
- Differential privacy
- Encryption technology
- AI access control
Targeted AI technology
- DNN
- CNN
- Contrastive learning
- FSL
- GNN
- Federated learning
- LSTM
- RNN
- Diffusion model
Task
- Classification
- Generation
Data
- Image
- Graph
- Audio
Related external influence aspect
References
Differential privacy
- Deep Learning with Differential Privacy, 2016
- Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data, 2017
- Learning Differentially Private Recurrent Language Models, 2018
- Efficient Deep Learning on Multi-Source Private Data, 2018
- Evaluating Differentially Private Machine Learning in Practice, 2019
- Tempered Sigmoid Activations for Deep Learning with Differential Privacy, 2020
Encryption technology
- Gazelle: A Low Latency Framework for Secure Neural Network Inference, 2018
- Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference, 2018
- nGraph-HE2: A High-Throughput Framework for Neural Network Inference on Encrypted Data, 2019
- Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network, 2021