This document discusses methods for enhancing data privacy through crypto clustering of heterogeneous and sensitive data. It first reviews existing literature on privacy-preserving techniques like local differential privacy and differential privacy-based clustering. It then proposes a method that uses cryptographic implementations based on sensitivity prediction and local differential privacy to automatically protect mixed data according to type and predicted sensitivity. Sensitive data is clustered and secured using these techniques to enhance privacy while maintaining data utility.