Machine Learning IP Protection | IEEE Conference Publication | IEEE Xplore

Machine Learning IP Protection


Abstract:

Machine learning, specifically deep learning is becoming a key technology component in application domains such as identity management, finance, automotive, and healthcar...Show More

Abstract:

Machine learning, specifically deep learning is becoming a key technology component in application domains such as identity management, finance, automotive, and healthcare, to name a few. Proprietary machine learning models - Machine Learning IP - are developed and deployed at the network edge, end devices and in the cloud, to maximize user experience. With the proliferation of applications embedding Machine Learning IPs, machine learning models and hyper-parameters become attractive to attackers, and require protection. Major players in the semiconductor industry provide mechanisms on device to protect the IP at rest and during execution from being copied, altered, reverse engineered, and abused by attackers. In this work we explore system security architecture mechanisms and their applications to Machine Learning IP protection.
Date of Conference: 05-08 November 2018
Date Added to IEEE Xplore: 03 January 2019
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Conference Location: San Diego, CA, USA

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