The rapid evolution of Internet-of-Things (IoT) technologies has led to an emerging need to make them smarter. A variety of applications now run simultaneously on an ARMbased processor. For example, devices on the edge of the Internet are provided with higher horsepower to be entrusted with storing, processing and analyzing data collected from IoT devices. This significantly improves efficiency and reduces the amount of data that needs to be transported to the cloud for data processing, analysis and storage. However, commodity OSes are prone to compromise. Once they are exploited, attackers can access the data on these devices. Since the data stored and processed on the devices can be sensitive, left untackled, this is particularly disconcerting. In this paper, we propose a new system, TrustShadow that shields legacy applications from untrusted OSes. Trust-Shadow takes advantage of ARM TrustZone technology and partitions resources into the secure and normal worlds. In the secure world, TrustShadow constructs a trusted execution environment for security-critical applications. This trusted environment is maintained by a lightweight runtime system that coordinates the communication between applications and the ordinary OS running in the normal world. The runtime system does not provide system services itself. Rather, it forwards requests for system services to the ordinary OS, and verifies the correctness of the responses. To demonstrate the efficiency of this design, we prototyped TrustShadow on a real chip board with ARM TrustZone support, and evaluated its performance using both microbenchmarks and real-world applications. We showed TrustShadow introduces only negligible overhead to real-world applications.
CITATION STYLE
Guan, L., Liu, P., Xing, X., Ge, X., Zhang, S., Yu, M., & Jaeger, T. (2017). TrustShadow: Secure execution of unmodified applications with ARM TrustZone. In MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (pp. 488–501). Association for Computing Machinery, Inc. https://doi.org/10.1145/3081333.3081349
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