Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, epsilon-differential privacy provides one of the strongest privacy guarantees and has no assumptions about an adversary's background knowledge. All the existing solutions that ensure epsilon-differential privacy handle the problem of disclosing relational and set-valued data in a privacy preserving manner separately. We developed an algorithm that considers both relational and set-valued data in differentially private disclosure of healthcare data.

Project Samples

Project Activity

See All Activity >

Categories

Machine Learning

License

Creative Commons Attribution License

Follow DiffGen

DiffGen Web Site

Other Useful Business Software
Ship Agents Faster Icon
Ship Agents Faster

Transform your applications and workflows into powerful agentic systems at global scale.

Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
Get Started Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of DiffGen!

Additional Project Details

Operating Systems

Windows

Intended Audience

Healthcare Industry

Programming Language

C++

Related Categories

C++ Machine Learning Software

Registered

2012-06-06