A non comparison oblivious sort and its application to k-NN

In this paper, we introduce an adaptation of the counting sort algorithm that leverages the data obliviousness of the algorithm to enable the sorting of encrypted data using Fully Homomorphic Encryption (FHE). Our approach represents the first known sorting algorithm for encrypted data that does not rely on comparisons. The implementation takes advantage of some basic operations on TFHE's Look-Up-Tables (LUT). We have integrated these operations into RevoLUT, a comprehensive open-source library built on tfhe-rs. We demonstrate the effectiveness of our Blind Counting Sort algorithm by developing a top-k selection algorithm and applying it to privacy-preserving k-Nearest Neighbors classification. This proves to be approximately 4 times faster than state-of-the-art methods.

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Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-05-19
DOI
https://doi.org/10.56553/popets-2025-0093
Citations
1
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
1.49
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article

A non comparison oblivious sort and its application to k-NN

Marc‐Olivier Killijian, Sofiane Azogagh, Félix Larose-Gervais
1 citations
Proceedings on Privacy Enhancing Technologies
Data Management and Algorithms
1.49
article

A non comparison oblivious sort and its application to k-NN

Marc‐Olivier Killijian, Sofiane Azogagh, Félix Larose-Gervais
article en
1 citations

Abstract

In this paper, we introduce an adaptation of the counting sort algorithm that leverages the data obliviousness of the algorithm to enable the sorting of encrypted data using Fully Homomorphic Encryption (FHE). Our approach represents the first known sorting algorithm for encrypted data that does not rely on comparisons. The implementation takes advantage of some basic operations on TFHE's Look-Up-Tables (LUT). We have integrated these operations into RevoLUT, a comprehensive open-source library built on tfhe-rs. We demonstrate the effectiveness of our Blind Counting Sort algorithm by developing a top-k selection algorithm and applying it to privacy-preserving k-Nearest Neighbors classification. This proves to be approximately 4 times faster than state-of-the-art methods.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(3)
Université du Québec à Montréal (CA)
Openalex Percentile: Top 19%
Data Management and Algorithms
1.49
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