An Exact Poly-Time Membership-Queries Algorithm for Extraction a three-Layer ReLU Network

• URL: http://arxiv.org/abs/2105.09673v1
• Date: Thu, 20 May 2021 11:24:08 GMT
• Title: An Exact Poly-Time Membership-Queries Algorithm for Extraction a three-Layer ReLU Network
• Authors: Amit Daniely and Elad Granot
• Abstract summary: As machine learning increasingly becomes more prevalent in our everyday life, many organizations offer neural-networks based services as a black-box. The reasons for hiding a learning model may vary: e.g., preventing copying of its behavior or keeping back an adversarial from reverse-engineering its mechanism. In this work, we show a neural-network algorithm that uses a number of queries to mimic precisely the behavior of a three-layer network that uses ReLU activation.
• Score: 38.91075212630913
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As machine learning increasingly becomes more prevalent in our everyday life, many organizations offer neural-networks based services as a black-box. The reasons for hiding a learning model may vary: e.g., preventing copying of its behavior or keeping back an adversarial from reverse-engineering its mechanism and revealing sensitive information about its training data. However, even as a black-box, some information can still be discovered by specific queries. In this work, we show a polynomial-time algorithm that uses a polynomial number of queries to mimic precisely the behavior of a three-layer neural network that uses ReLU activation.

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