7 Privacy-preserving data mining and management techniques (Part-1)
- The importance of privacy preservation in data mining besides today’s data privacy regulations and requirements
- Widely used privacy protection mechanisms and their characteristics in data mining operations when processing and publishing data
- Various methods of applying privacy-enhancing techniques of data mining in practice, based on different application requirements
- Implementing privacy techniques in data mining with Python
7.1 The Importance of Privacy Preservation in Data Mining and Management
7.2 Privacy Protection in Data Processing and Mining
7.2.1 What is Data Mining and How it can Help?
7.2.2 Impact of Privacy Regulatory Requirements
7.3 Protecting Privacy by Modifying the Input
7.3.1 Applications and the Limitations
7.4 Protecting Privacy when Publishing Data
7.4.1 Implementing Data Sanitization Operations in Python
7.4.2 k-anonymity
7.4.3 Implementing k-anonymity in Python
7.5 Summary