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Optimal Oblivious Algorithms for Multi-Way Joins

Authors Xiao Hu , Zhiang Wu

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Xiao Hu
  • University of Waterloo, Canada
Zhiang Wu
  • University of Waterloo, Canada

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Xiao Hu and Zhiang Wu. Optimal Oblivious Algorithms for Multi-Way Joins. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 25:1-25:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ICDT.2025.25

Abstract

In cloud databases, cloud computation over sensitive data uploaded by clients inevitably causes concern about data security and privacy. Even if cryptographic primitives and trusted computing environments are integrated into query processing to safeguard the actual contents of the data, access patterns of algorithms can still leak private information about data. Oblivious RAM (ORAM) and circuits are two generic approaches to address this issue, ensuring that access patterns of algorithms remain oblivious to the data. However, deploying these methods on insecure algorithms, particularly for multi-way join processing, is computationally expensive and inherently challenging. 
In this paper, we propose a novel sorting-based algorithm for multi-way join processing that operates without relying on ORAM simulations or other security assumptions. Our algorithm is a non-trivial, provably oblivious composition of basic primitives, with time complexity matching the insecure worst-case optimal join algorithm, up to a logarithmic factor. Furthermore, it is cache-agnostic, with cache complexity matching the insecure lower bound, also up to a logarithmic factor. This clean and straightforward approach has the potential to be extended to other security settings and implemented in practical database systems.

Subject Classification

ACM Subject Classification
  • Security and privacy → Management and querying of encrypted data
  • Information systems → Join algorithms
Keywords
  • oblivious algorithms
  • multi-way joins
  • worst-case optimality

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