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Defusing the Tension between Security and Performance with Secure Microarchitectures

. University of California, San Diego, USA, (2022)

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Shredder: Learning Noise to Protect Privacy with Partial DNN Inference on the Edge., , , , and . CoRR, (2019)Going beyond the Limits of SFI: Flexible and Secure Hardware-Assisted In-Process Isolation with HFI., , , , , , , , , and 2 other author(s). ASPLOS (3), page 266-281. ACM, (2023)I See Dead µops: Leaking Secrets via Intel/AMD Micro-Op Caches., , , , , and . ISCA, page 361-374. IEEE, (2021)Hardware-Assisted Fault Isolation: Going Beyond the Limits of Software-Based Sandboxing., , , , , , , , , and 2 other author(s). IEEE Micro, 44 (4): 70-79 (July 2024)Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy., , , , , and . WWW, page 669-680. ACM / IW3C2, (2021)Privacy in Deep Learning: A Survey., , , , , and . CoRR, (2020)A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference., , , , , and . CoRR, (2020)Mobilizing the Micro-Ops: Exploiting Context Sensitive Decoding for Security and Energy Efficiency., , and . ISCA, page 624-637. IEEE Computer Society, (2018)TooT: an efficient and scalable power-gating method for NoC routers., , , and . NOCS, page 1-8. IEEE, (2016)NVLeak: Off-Chip Side-Channel Attacks via Non-Volatile Memory Systems., , , , , and . USENIX Security Symposium, page 6771-6788. USENIX Association, (2023)