RV2GC: Reconstructing the Garbling Boundary in a RISC-V Garbled Processor
Programmable garbled-circuit execution must balance the benefits of cross-program reuse against the cost of repeated wor
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← 返回所有主题Programmable garbled-circuit execution must balance the benefits of cross-program reuse against the cost of repeated wor
Register-Transfer Level (RTL) simulators are fundamental to modern IC design workflows, yet like any complex software, t
Fully Homomorphic Encryption (FHE) enables computation on encrypted data and is promising for privacy-preserving computi
Deep neural networks (DNNs) are widely deployed in safety- and privacy-critical domains such as healthcare and finance,
Hardware malware detectors (HMDs) classify hardware performance-counter measurements to identify malicious execution. Fa
Multi-trigger backdoor attacks, in which heterogeneous trigger mechanisms (e.g., patch, blend, warping, and the latent-d
Privacy-preserving machine learning (PPML) offers a promising path toward bringing powerful AI services to the edge with
Homomorphic encryption allows a computing service to process encrypted data, but the client must first encode and encryp
Ensuring data security in the era of Artificial Intelligence (AI) and deepfake technology requires robust biometric syst
NVIDIA's Grace Hopper (GH200) superchip represents a new generation of heterogeneous computing, tightly integrating a 72
Microarchitectural attacks such as Spectre and Meltdown undermine security by exploiting software-visible side effects o
A wide range of important cloud applications, e.g., database analytics, graph analytics, and genome analysis, spend a co
Smart meters are pivotal to the functioning of smart grids, as they measure and transmit energy consumption data that in
Hardware malware detectors (HMDs) classify programs as benign or malicious based on hardware performance counter (HPC) d
The growth of the Internet of Things (IoT) has raised concerns over the privacy of data collected by resource-constraine
Efficient post-quantum cryptography on resource-constrained Internet-of-Things (IoT) devices requires implementations th
Increasing connectivity to the outside world and the lack of inbuilt security mechanisms have made legacy intra-vehicula
DRAM continues to limit the performance, energy efficiency, and robustness of modern systems. Many prior works propose D
分割计算(Split Computing, SC)通过在边缘设备与云服务器之间切分深度神经网络(DNN)推理来降低端侧算力与延迟压力,但切分点处传输的中间特征表示同时暴露于两类风险:其一是硬件故障(如瞬态位翻转、软错误)导致的推理精度退化,
Recent studies have shown that most commercial direct time-of-flight (dToF) LiDARs can be spoofed by injecting high-freq