1. 1 Random Data Perturbation Techniques and Privacy Preserving Data Mining Gunjan Gupta (Authors: H. Kargupta, S. Datta, Q. Wang & K. Sivakumar) April 26, 2005
2. 2 Privacy & Good Service: Often Conflicting Goals • Privacy – Customer: I don’t want you to share my personal information with anyone. – Business: I don’t want to share my data with a competitor. • Quantity, Cost & Quality of Service – Customer: I want you to provide me lower cost of service – and good quality. – and at lower cost. • Paradox: lower cost often comes from being able to use/share sensitive data that can be used or misused: – Provide better service by predicting consumer needs better, or sell information to marketers. – Optimize load sharing between competing utilities or preempting competition. – Doctor saving patient by knowing patient history or insurance companies declining coverage to individuals with preexisting conditions.
3. 3 Can we use privacy sensitive data to optimize cost and quality of a service without compromising any privacy? Central Question: