Data Privacy

  1. Data Privacy in Data Science and Machine Learning
    1. Ethical Data Sourcing and Collection
      1. Data Minimization in Datasets
        1. Feature Selection
          1. Sample Size Optimization
            1. Temporal Limitations
            2. Use of Public vs. Private Data
              1. Public Dataset Considerations
                1. Terms of Use Compliance
                  1. Ethical Use Guidelines
                  2. Data Provenance and Lineage
                    1. Source Documentation
                      1. Chain of Custody
                        1. Quality Assessments
                      2. Privacy Risks in the ML Lifecycle
                        1. Training Data Exposure
                          1. Data Leakage Risks
                            1. Overfitting to Sensitive Data
                              1. Model Memorization
                                1. Inference Attacks
                                2. Mitigation Strategies
                                  1. Data Sanitization
                                    1. Regularization Techniques
                                      1. Privacy-Preserving Training
                                    2. Model Inversion Attacks
                                      1. Attack Methods
                                        1. Gradient-Based Inversion
                                          1. Optimization-Based Attacks
                                            1. Generative Model Attacks
                                            2. Mitigation Strategies
                                              1. Output Perturbation
                                                1. Model Distillation
                                                  1. Access Control
                                                2. Membership Inference Attacks
                                                  1. Attack Scenarios
                                                    1. Binary Membership Inference
                                                      1. Property Inference
                                                        1. Attribute Inference
                                                        2. Defense Mechanisms
                                                          1. Differential Privacy
                                                            1. Model Regularization
                                                              1. Ensemble Methods
                                                            2. Model Stealing
                                                              1. Threat Vectors
                                                                1. Query-Based Extraction
                                                                  1. Side-Channel Attacks
                                                                    1. Insider Threats
                                                                    2. Prevention Techniques
                                                                      1. Query Limiting
                                                                        1. Output Obfuscation
                                                                          1. Watermarking
                                                                        2. Adversarial Attacks
                                                                          1. Evasion Attacks
                                                                            1. Poisoning Attacks
                                                                              1. Privacy Implications
                                                                            2. Privacy-Preserving Machine Learning (PPML)
                                                                              1. Federated Learning
                                                                                1. Architecture and Workflow
                                                                                  1. Centralized Coordination
                                                                                    1. Local Model Training
                                                                                      1. Model Aggregation
                                                                                      2. Privacy Benefits and Challenges
                                                                                        1. Data Localization
                                                                                          1. Communication Privacy
                                                                                            1. Inference Attacks
                                                                                            2. Implementation Considerations
                                                                                              1. Client Selection
                                                                                                1. Communication Efficiency
                                                                                                  1. Heterogeneity Handling
                                                                                                2. Encrypted Computation
                                                                                                  1. Secure Computation Techniques
                                                                                                    1. Homomorphic Encryption
                                                                                                      1. Secure Multi-Party Computation
                                                                                                        1. Trusted Execution Environments
                                                                                                        2. Performance Considerations
                                                                                                          1. Computational Overhead
                                                                                                            1. Communication Costs
                                                                                                              1. Scalability Limitations
                                                                                                            2. Secure Multi-Party Computation (SMPC)
                                                                                                              1. Protocols and Applications
                                                                                                                1. Secret Sharing Schemes
                                                                                                                  1. Garbled Circuits
                                                                                                                    1. Oblivious Transfer
                                                                                                                    2. ML Applications
                                                                                                                      1. Private Set Intersection
                                                                                                                        1. Secure Aggregation
                                                                                                                          1. Private Model Training
                                                                                                                        2. Using Differentially Private Data for Training
                                                                                                                          1. Implementation Approaches
                                                                                                                            1. Input Perturbation
                                                                                                                              1. Algorithm Perturbation
                                                                                                                                1. Output Perturbation
                                                                                                                                2. Privacy-Utility Trade-offs
                                                                                                                                  1. Noise Calibration
                                                                                                                                    1. Utility Metrics
                                                                                                                                      1. Optimization Strategies
                                                                                                                                  2. Model Explainability and Fairness
                                                                                                                                    1. Algorithmic Bias and Discrimination
                                                                                                                                      1. Sources of Bias
                                                                                                                                        1. Historical Bias
                                                                                                                                          1. Representation Bias
                                                                                                                                            1. Measurement Bias
                                                                                                                                              1. Evaluation Bias
                                                                                                                                              2. Mitigation Techniques
                                                                                                                                                1. Bias Detection Methods
                                                                                                                                                  1. Fairness Constraints
                                                                                                                                                    1. Algorithmic Auditing
                                                                                                                                                  2. The Right to Explanation
                                                                                                                                                    1. Technical Approaches
                                                                                                                                                      1. Model-Agnostic Methods
                                                                                                                                                        1. Local Explanations
                                                                                                                                                          1. Global Explanations
                                                                                                                                                        2. Fairness Metrics
                                                                                                                                                          1. Individual Fairness
                                                                                                                                                            1. Group Fairness
                                                                                                                                                              1. Counterfactual Fairness
                                                                                                                                                              2. Privacy-Preserving Explanations
                                                                                                                                                                1. Explanation Privacy
                                                                                                                                                                  1. Differential Privacy for Explanations
                                                                                                                                                                    1. Secure Explanation Generation

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                                                                                                                                                                5. Data Privacy Governance and Management

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                                                                                                                                                                7. Emerging Topics and Future Challenges