Presentation
Order-Preserving Cryptography for the Confidential Inference in Random Forests: FPGA Design and Implementation
DescriptionPrior work has addressed the problem of confidential inference in decision trees. Both traditional order-preserving cryptography and order-preserving NTRU cryptography have been used to ensure data and model privacy in decision trees. Furthermore, FPGA architectures and implementations have been proposed for implementing such confidential inference algorithms on limited resource, edge platforms such as low-cost FPGA boards. In this paper, we address the challenging problem of scalability of order-preserving confidential inference to random forests, which are ensembles of decision trees that are meant to improve their classification accuracy and reduce their overfitting. The paper develops a methodology and an FPGA implementation strategy for scaling up order-preserving cryptography to random forests. In particular, a framework is used to study the multifaceted tradeoffs that exist between the number of trees in the random forest, the strength of the encryption, the accuracy of the inferences, and the resources of the edge platform. Extensive experiments are conducted using the MNIST dataset and the Intel DE10 Standard FPGA board.
Event Type
Research Manuscript
TimeWednesday, June 2610:45am - 11:00am PDT
Location3001, 3rd Floor
AI
AI/ML Algorithms