2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

Paper Detail

Paper IDIFS-6.4
Paper Title SCALABLE PRIVACY-PRESERVING DISTRIBUTED EXTREMELY RANDOMIZED TREES FOR STRUCTURED DATA WITH MULTIPLE COLLUDING PARTIES
Authors Amin Aminifar, Western Norway University of Applied Sciences, Norway; Fazle Rabbi, University of Bergen, Western Norway University of Applied Sciences, Norway; Yngve Lamo, Western Norway University of Applied Sciences, Norway
SessionIFS-6: Anonymization, Security and Privacy
LocationGather.Town
Session Time:Thursday, 10 June, 15:30 - 16:15
Presentation Time:Thursday, 10 June, 15:30 - 16:15
Presentation Poster
Topic Information Forensics and Security: [ADP] Anonymization And Data Privacy
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Virtual Presentation  Click here to watch in the Virtual Conference
Abstract Today, in many real-world applications of machine learning algorithms, the data is stored on multiple sources instead of at one central repository. In many such scenarios, due to privacy concerns and legal obligations, e.g., for medical data, and communication/computation overhead, for instance for large scale data, the raw data cannot be transferred to a center for analysis. Therefore, new machine learning approaches are proposed for learning from the distributed data in such settings. In this paper, we extend the distributed Extremely Randomized Trees (ERT) approach w.r.t. privacy and scalability. First, we extend distributed ERT to be resilient w.r.t. the number of colluding parties in a scalable fashion. Then, we extend the distributed ERT to improve its scalability without any major loss in classification performance. We refer to our proposed approach as k-PPD-ERT or Privacy-Preserving Distributed Extremely Randomized Trees with $k$ colluding parties.