<ul><li>On-device deep learning (DL) has gained popularity in mobile apps for offline model inference and user privacy preservation.</li><li>However, it introduces vulnerabilities related to model-stealing attacks and intellectual property infringement.</li><li>A proposed solution called THEMIS lifts the read-only restriction of on-device DL models and protects the model owner's intellectual property.</li><li>Experimental results and investigation of real-world DL mobile apps demonstrate the practicality and effectiveness of THEMIS.</li></ul>

THEMIS: Towards Practical Intellectual Property Protection for Post-Deployment On-Device Deep Learning Models

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