Let’s stride blindfolded in a forest : sublinear multi-client decision trees evaluation

• Main Authors: Ma, Jack P. K., Tai, Raymond K. H., Zhao, Yongjun, Chow, Sherman S. M.
• Other Authors: Network and Distributed Systems Security (NDSS) Symposium 2021
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Computer science and engineering; Privacy-preserving Technology; Machine Learning
• Online Access: https://hdl.handle.net/10356/148326
• Institution: Nanyang Technological University

Decision trees are popular machine-learning classification models due to their simplicity and effectiveness. Tai et al. (ESORICS ’17) propose a privacy-preserving decision-tree evaluation protocol purely based on additive homomorphic encryption, without introducing dummy nodes for hiding the tree s...