research-article

PrivPy: General and Scalable Privacy-Preserving Data Mining

Authors:

Wei XuAuthors Info & Claims

KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Pages 1299 - 1307

https://doi.org/10.1145/3292500.3330920

Published: 25 July 2019 Publication History

Abstract

Privacy is a big hurdle for collaborative data mining across multiple parties. We present multi-party computation (MPC) framework designed for large-scale data mining tasks. PrivPy combines an easy-to-use and highly flexible Python programming interface with state-of-the-art secret-sharing-based MPC backend. With essential data types and operations (such as NumPy arrays and broadcasting), as well as automatic code-rewriting, programmers can write modern data mining algorithms conveniently in familiar Python. We demonstrate that we can support many real-world machine learning algorithms (e.g. logistic regression and convolutional neural networks) and large datasets (e.g. 5000-by-1-million matrix) with minimal algorithm porting effort.

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Cited By

Guo GZhu YChen CZhang LFeng RMa D(2024)Privacy-Preserving Queries Using Multisource Private Data Counting on Real Numbers in IoTIEEE Internet of Things Journal10.1109/JIOT.2023.332966011:7(11353-11367)Online publication date: 1-Apr-2024
https://doi.org/10.1109/JIOT.2023.3329660
Jaberi MMala H(2024)Privacy-preserving eigenvector computation with applications in spectral clusteringInternational Journal of Information Technology10.1007/s41870-024-01815-zOnline publication date: 5-Apr-2024
https://doi.org/10.1007/s41870-024-01815-z
Dong YChen XSong XLi K(2023)FlexBNN: Fast Private Binary Neural Network Inference With Flexible Bit-WidthIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326534218(2382-2397)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3265342
Show More Cited By

Index Terms

PrivPy: General and Scalable Privacy-Preserving Data Mining
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination
2. Security and privacy
  1. Security services
    1. Privacy-preserving protocols

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Published In

cover image ACM Conferences

KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

July 2019

3305 pages

ISBN:9781450362016

DOI:10.1145/3292500

General Chairs:
Ankur Teredesai
KenSci
,
Vipin Kumar
University of Minnesota
,
Program Chairs:
Ying Li
EV Analysis Corporation
,
Rómer Rosales
LinkedIn
,
Evimaria Terzi
Boston University
,
George Karypis
University of Minnesota

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 July 2019

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National Natural Science Foundation of China

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KDD '19

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KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

August 4 - 8, 2019

AK, Anchorage, USA

Acceptance Rates

KDD '19 Paper Acceptance Rate 110 of 1,200 submissions, 9%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Guo GZhu YChen CZhang LFeng RMa D(2024)Privacy-Preserving Queries Using Multisource Private Data Counting on Real Numbers in IoTIEEE Internet of Things Journal10.1109/JIOT.2023.332966011:7(11353-11367)Online publication date: 1-Apr-2024
https://doi.org/10.1109/JIOT.2023.3329660
Jaberi MMala H(2024)Privacy-preserving eigenvector computation with applications in spectral clusteringInternational Journal of Information Technology10.1007/s41870-024-01815-zOnline publication date: 5-Apr-2024
https://doi.org/10.1007/s41870-024-01815-z
Dong YChen XSong XLi K(2023)FlexBNN: Fast Private Binary Neural Network Inference With Flexible Bit-WidthIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326534218(2382-2397)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3265342
Yu XFeng JZhao WYang HTang D(2023)Peer-to-peer privacy-preserving vertical federated learning without trusted third-party coordinatorPeer-to-Peer Networking and Applications10.1007/s12083-023-01512-x16:5(2242-2255)Online publication date: 12-Jul-2023
https://doi.org/10.1007/s12083-023-01512-x
Jaberi MMala H(2023)Privacy-preserving multi-party PCA computation on horizontally and vertically partitioned data based on outsourced QR decompositionThe Journal of Supercomputing10.1007/s11227-023-05206-279:13(14358-14387)Online publication date: 6-Apr-2023
https://doi.org/10.1007/s11227-023-05206-2
Dai TDuan LJiang YLi YMei FSun Y(2023)Force: Highly Efficient Four-Party Privacy-Preserving Machine Learning on GPUSecure IT Systems10.1007/978-3-031-47748-5_18(330-349)Online publication date: 8-Nov-2023
https://doi.org/10.1007/978-3-031-47748-5_18
Guo JShuai MWang QLi WLin J(2023)Replicated Additive Secret Sharing with the Optimized Number of SharesSecurity and Privacy in Communication Networks10.1007/978-3-031-25538-0_20(371-389)Online publication date: 4-Feb-2023
https://doi.org/10.1007/978-3-031-25538-0_20
Leung C(2022)Big Data Mining and Analytics With MapReduceEncyclopedia of Data Science and Machine Learning10.4018/978-1-7998-9220-5.ch010(156-172)Online publication date: 14-Oct-2022
https://doi.org/10.4018/978-1-7998-9220-5.ch010
Leung C(2022)Big Data Analytics and Mining for Knowledge DiscoveryResearch Anthology on Big Data Analytics, Architectures, and Applications10.4018/978-1-6684-3662-2.ch033(708-721)Online publication date: 2022
https://doi.org/10.4018/978-1-6684-3662-2.ch033
Fan XChen KWang GZhuang MLi YXu WYin HStavrou ACremers CShi E(2022)NFGenProceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security10.1145/3548606.3560565(995-1008)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3548606.3560565
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