4 Local differential privacy for machine learning
This chapter covers
- Local differential privacy (LDP)
- Implementing the randomized response mechanism for LDP
- LDP mechanisms for one-dimensional data frequency estimation
- Implementing and experimenting with different LDP mechanisms for one-dimensional data
In the previous two chapters we discussed centralized differential privacy (DP), where there is a trusted data curator who collects data from individuals and applies different techniques to obtain differentially private statistics about the population. Then the curator publishes privacy-preserving statistics about this population. However, these techniques are unsuitable when individuals do not completely trust the data curator. Hence, various ...
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