Assuring privacy when big brother is watching

Homeland security measures are increasing the amount of data collected, processed and mined. At the same time, owners of the data raised legitimate concern about their privacy and potential abuses of the data. Privacy-preserving data mining techniques enable learning models without violating privacy. This paper addresses a complementary problem: What if we want to apply a model without revealing it? This paper presents a method to apply classification rules without revealing either the data or the rules. In addition, the rules can be verified not to use “forbidden” criteria. Keywords Privacy, Security, Profiling

• Type: Conference
• Year: 2003
• Where: DMKD
• Authors: Murat Kantarcioglu, Chris Clifton
• Keywords: Data Mining Techniques, DMKD 2003, Enable Learning Models, Homeland Security Measures