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Creators/Authors contains: "Zhao, Jishen"

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  1. ; ; (, MEMSYS)
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  2. ; ; ; ; ; (, USENIX Conference on Security Symposium)
    Accepted Manuscript Full Text Available
  3. ; ; ; ; (, IEEE Design & Test)
    Recent advances in model piracy have uncovered a new security hole for malicious attacks endangering the Intellectual Property (IP) of Deep Learning (DL) systems. This manuscript features our research titled “DeepAttest: An End-toEnd Attestation Framework for Deep Neural Networks” [1] that is selected for the 2021 Top Picks in hardware and embedded security. DeepAttest is the first end-to-end framework that achieves reliable and efficient IP protection of DL devices with hardware-bounded usage control. We leverage device-specific model fingerprinting and Trusted Execution Environment (TEE) to ensure that only DL models with the device-specific fingerprint can run inference on protected hardware 
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  4. ; ; ; (, International Symposium on High-Performance Computer Architecture (HPCA))
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  5. ; ; ; ; ; ; ; (, ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED))
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  6. ; ; ; ; ; (, IEEE/ACM International Symposium on Microarchitecture (MICRO))
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  7. ; ; ; ; (, ACM SIGOPS Asia-Pacific Workshop on Systems (APSys))
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  8. ; ; ; ; ; (, Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design)
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  9. ; ; ; (, IEEE International Symposium on Workload Characterization)
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  10. ; ; ; ; (, International Symposium on Memory Systems)
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