35,309 research outputs found
Measuring the Impact of Spectre and Meltdown
The Spectre and Meltdown flaws in modern microprocessors represent a new
class of attacks that have been difficult to mitigate. The mitigations that
have been proposed have known performance impacts. The reported magnitude of
these impacts varies depending on the industry sector and expected workload
characteristics. In this paper, we measure the performance impact on several
workloads relevant to HPC systems. We show that the impact can be significant
on both synthetic and realistic workloads. We also show that the performance
penalties are difficult to avoid even in dedicated systems where security is a
lesser concern
Dataset for hardware Trojan detection
Nowadays, cloud services rely extensively on the use of virtual machines to enforce security by isolation. However, hardware trojan attacks break this assumption. Within these attacks, cache side-channel attacks such as Spectre and Meltdown are the focus of this work. In this project, we develop a set of tools to generate a dataset; and a dataset that will allow the use of Machine Learning techniques to detect Spectre and Meltdown attacks (i.e. using a cache side-channel). When released, this dataset will enable researchers to compare their ML-based detection proposals based on the same dataset (which is not currently the case). Also, it eliminates the need of an infected computer to generate the attacks and the corresponding dataset for subsequent research studies
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