A Framework for Testing and Evaluating Secure and Verifiable Computational Offloading in Edge Computing



Crowley, Thomas B

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Throughout the world, 8.74 billion Internet of Things (IoT) devices have been deployed, ranging from household thermostats to sensors in remote areas. However, these IoT devices are resource-constrained, not only in computational speed, but often in available electrical power. Computational offloading can provide significant power and latency savings, but often exposes data and systems to security breaches. Researchers have proposed a plethora of protocols to address these security gaps. These published works focus solely on theoretical power and latency savings and do not include end-to-end implementation or data. Furthermore, few, if any, of these protocols have been fielded by either academic or commercial projects. This paper presents the results from the end-to-end implementation of an encryption offloading protocol. Latency and power data were collected to enable comparisons of security computations done solely on the IoT device and partially outsourced to a nearby device. Using the analysis of this data and lessons learned from the end-to-end implementation, the author of this research also created a generic software library to implement computational offloading to the edge. The new software library enabled the integration of a known, secure and verifiable computing technique into the encryption offloading protocol.



Internet of Things, Edge computing, Trusted execution environment, Computational offloading, Gramine