Paper 2024/1065

AITIA: Efficient Secure Computation of Bivariate Causal Discovery

Truong Son Nguyen, Arizona State University
Lun Wang, University of California, Berkeley
Evgenios M. Kornaropoulos, George Mason University
Ni Trieu, Arizona State University
Abstract

Researchers across various fields seek to understand causal relationships but often find controlled experiments impractical. To address this, statistical tools for causal discovery from naturally observed data have become crucial. Non-linear regression models, such as Gaussian process regression, are commonly used in causal inference but have limitations due to high costs when adapted for secure computation. Support vector regression (SVR) offers an alternative but remains costly in an Multi-party computation context due to conditional branches and support vector updates. In this paper, we propose Aitia, the first two-party secure computation protocol for bivariate causal discovery. The protocol is based on optimized multi-party computation design choices and is secure in the semi-honest setting. At the core of our approach is BSGD-SVR, a new non-linear regression algorithm designed for MPC applications, achieving both high accuracy and low computation and communication costs. Specifically, we reduce the training complexity of the non-linear regression model from approximately from $\mathcal{O}(N^3)$ to $\mathcal{O}(N^2)$ where $N$ is the number of training samples. We implement Aitia using CrypTen and assess its performance across various datasets. Empirical evaluations show a significant speedup of $3.6\times$ to $340\times$ compared to the baseline approach.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Published elsewhere. Minor revision. ACM Conference on Computer and Communications Security (CCS) 2024
DOI
10.1145/3658644.3670337
Keywords
Secure Machine LearningCausal DiscoveryCausal InferenceMulti-party ComputationSupport Vector Regression
Contact author(s)
snguye63 @ asu edu
wanglun @ berkeley edu
evgenios @ gmu edu
ntrieu1 @ asu edu
History
2024-07-01: approved
2024-06-30: received
See all versions
Short URL
https://ia.cr/2024/1065
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2024/1065,
      author = {Truong Son Nguyen and Lun Wang and Evgenios M. Kornaropoulos and Ni Trieu},
      title = {{AITIA}: Efficient Secure Computation of Bivariate Causal Discovery},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/1065},
      year = {2024},
      doi = {10.1145/3658644.3670337},
      url = {https://eprint.iacr.org/2024/1065}
}
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