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Shredder: Learning Noise Distributions to Protect Inference Privacy.

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I See Dead µops: Leaking Secrets via Intel/AMD Micro-Op Caches., , , , , and . ISCA, page 361-374. IEEE, (2021)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)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)SecSMT: Securing SMT Processors against Contention-Based Covert Channels., , , and . USENIX Security Symposium, page 3165-3182. USENIX Association, (2022)Shredder: Learning Noise Distributions to Protect Inference Privacy., , , , , and . ASPLOS, page 3-18. ACM, (2020)ASPLOS 2020 was canceled because of COVID-19..Context-Sensitive Decoding: On-Demand Microcode Customization for Security and Energy Management., , and . IEEE Micro, 39 (3): 75-83 (2019)Defusing the Tension between Security and Performance with Secure Microarchitectures. University of California, San Diego, USA, (2022)Context-Sensitive Fencing: Securing Speculative Execution via Microcode Customization., , and . ASPLOS, page 395-410. ACM, (2019)