On the Attribute Hiding Security of Privacy Preserving Secret-Sharing-Based Outsourced Decision Tree Classification

Summary

Researchers identify an attribute leakage flaw in SecDT, a secret-sharing framework for outsourced decision tree inference, where node attributes are exposed to non-owner parties. They propose SecDT+v1 and SecDT+v2, which use the transformation matrix technique to obfuscate attributes, and SecDT+vH and SecDT+vDP, which add dot-product operations to hide attribute access patterns. Evaluations on real-world datasets report better classification latency and bandwidth efficiency than prior solutions.

Mitigation

The paper proposes SecDT+v1 and SecDT+v2 (transformation matrix obfuscation of node attributes) and SecDT+vH and SecDT+vDP (dot-product operations to hide attribute access patterns) as enhancements to SecDT.

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