Related papers: OpenCCA: An Open Framework to Enable Arm CCA Resea…
Arm introduced the Confidential Compute Architecture (CCA) in the upcoming Armv9-A architecture, enabling the support of confidential virtual machines (CVMs) in a separate world called the Realm world, providing protection from untrusted…
Novel confidential computing technologies such as Intel TDX, AMD SEV, and Arm CCA have recently emerged. In practice, due to its minimal trust boundaries, Intel SGX still remains widely used for enclave-based applications in cloud…
Trusted execution environments in several existing and upcoming CPUs demonstrate the success of confidential computing, with the caveat that tenants cannot securely use accelerators such as GPUs and FPGAs. In this paper, we reconsider the…
Attacks based on side-channel analysis (SCA) pose a severe security threat to modern computing platforms, further exacerbated on IoT devices by their pervasiveness and handling of private and critical data. Designing SCA-resistant computing…
Deploying machine learning (ML) models on user devices can improve privacy (by keeping data local) and reduce inference latency. Trusted Execution Environments (TEEs) are a practical solution for protecting proprietary models, yet existing…
Arm Confidential Computing Architecture (CCA) currently isolates at the granularity of an entire Confidential Virtual Machine (CVM), leaving intra-VM bugs such as Heartbleed unmitigated. The state-of-the-art narrows this to the process…
Micro-controller units (MCUs) implement the de facto interface between the physical and digital worlds. As a consequence, they appear in a variety of sensing/actuation applications, from smart personal spaces to complex industrial control…
Timing-based side and covert channels in processor caches continue to be a threat to modern computers. This work shows for the first time a systematic, large-scale analysis of Arm devices and the detailed results of attacks the processors…
Software composition analysis (SCA) denotes the process of identifying open-source software components in an input software application. SCA has been extensively developed and adopted by academia and industry. However, we notice that the…
Confidential Virtual Machines (CVMs) are increasingly adopted to protect sensitive workloads from privileged adversaries such as the hypervisor. While they provide strong isolation guarantees, existing CVM architectures lack first-class…
Confidential containers protect cloud-native workloads using trusted execution environments (TEEs). However, existing Container-in-TEE designs (e.g., Confidential Containers (CoCo)) encapsulate the entire runtime within the TEE, inflating…
Although Cooperative Driving Automation (CDA) has attracted considerable attention in recent years, there remain numerous open challenges in this field. The gap between existing simulation platforms that mainly concentrate on single-vehicle…
Digital Compute-in-Memory (DCiM) accelerates neural networks by reducing data movement. Approximate DCiM can further improve power-performance-area (PPA), but demands accuracy-constrained co-optimization across coupled architecture and…
The rapid advancement of cloud-native technologies has created an urgent need for security. Currently, confidential containers are increasingly deployed in multi-tenant environments. Existing confidential container designs mainly adopt a…
Application performance of modern day processors is often limited by the memory subsystem rather than actual compute capabilities. Therefore, data throughput specifications play a key role in modeling application performance and determining…
The Apollo Advanced Telecommunications Computing Architecture (ATCA) platform is an open-source design consisting of a generic "Service Module" (SM) and a customizable "Command Module" (CM), allowing for cost-effective use in applications…
With the rapid development of scientific computation, more and more researchers and developers are committed to implementing various workloads/operations on different devices. Among all these devices, NVIDIA GPU is the most popular choice…
Useful models of loop kernel runtimes on out-of-order architectures require an analysis of the in-core performance behavior of instructions and their dependencies. While an instruction throughput prediction sets a lower bound to the kernel…
In recent years, Arm-based processors have arrived on the HPC scene, offering an alternative the existing status quo, which was largely dominated by x86 processors. In this paper, we evaluate the Arm ecosystem, both the hardware offering…
Static Random-Access Memory (SRAM) yield analysis is essential for semiconductor innovation, yet research progress faces a critical challenge: the large gap between simplified academic models and the complexities observed in practice. The…