Work

Poster: Practical Privacy-Preserving Decision Tree Evaluation for Resource-Constrained Devices

Year: 2024

Type: conference-paper

Abstract: We investigate the problem of private decision tree evaluation, which involves a server who holds a private decision tree, and a client who wants to classify its private attribute vector on the decision tree. The goal is to enable the client to learn the classification result while revealing nothing about both parties' inputs. We propose a novel secure two-party protocol for the problem of private decision tree evaluation based on symmetric encryption and oblivious transfer, which achieves higher efficiency and can be applied to scenarios involving resource-constrained devices.

Source: ACM Conference on Embedded Networked Sensor Systems (SenSys)

DOI: 10.1145/3666025.3699391

Authors: Yuan Xue, Fan Jin, Xiangyou Bei

Language: English

Topic: Cryptography and Data Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4404034626

FWCI:

Cites: 2

Cited by:

Related to: 10