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uSFI: Ultra-lightweight software fault isolation for IoT-class devices

Authors: Todd Austin; Zelalem Birhanu Aweke;

uSFI: Ultra-lightweight software fault isolation for IoT-class devices

Abstract

Embedded device security is a particularly difficult challenge, as the quantity of devices makes them attractive targets, while their cost-sensitive design leads to less-than-desirable security implementations. Most current low-end embedded devices do not include any form of security or only include simple memory protection support. One line of research in crafting low-cost security for low-end embedded devices has focused on sand-boxing trusted code from untrusted code using both hardware and software techniques. These previous attempts suffer from large trusted code bases (e.g., including the entire kernel), high runtime overheads (e.g., due to code instrumentation), partial protection (e.g., only provide write protection), or heavyweight hardware modifications. In this work, we leverage the rudimentary memory protection support found in modern IoT-class microcontrollers to build a low-profile, low-overhead, flexible sandboxing mechanism that can provide isolation between tightly-coupled software modules. With our approach, named uSFI, only the trust management code must be trusted. Through the use of a static verifier and monitored inter-module transitions, module code at all privilege levels (including the kernel) is able to run uninstrumented and untrusted code. We implemented uSFI on an ARMv7-M based processor, both bare metal and running the freeRTOS kernel, and analyzed the performance using the MiBench embedded benchmark suite and two additional highly detailed applications. We found that performance overheads were minimal, with at most 1.1% slowdown, and code size overheads were also low, at a maximum of 10%. In addition, our trusted code base is trivially small at only 150 lines of code.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average