Evaluating the performance of Ascon lightweight authenticated encryption for AI-enabled IoT devices

Khan, Safiullah ORCID: https://orcid.org/0000-0001-8342-6928, Lee, Wai-Kong and Hwang, Seong Oun (2022) Evaluating the performance of Ascon lightweight authenticated encryption for AI-enabled IoT devices. In: 2022 TRON Symposium (TRONSHOW), 7 December 2022 - 9 December 2022, Tokyo, Japan.

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Abstract

Internet of Things (IoTs) have proliferated our daily lives with numerous applications ranging from smart appliances to smart cities. IoT devices exchange sensor data by connecting to an IoT gateway or other edge device. The data is then sent to the cloud for analysis. For some critical applications, the delay introduced by data transfer to cloud is unacceptable. To reduce this delay, the computations are carried out closer to the IoT devices. In order to analyze the data locally on the IoT device, some kind of intelligence is required to be incorporated on the IoT device, making it AI-enabled IoT device. The analyzed data carry more information and needs to be encrypted if needed to send over the network. Lightweight authenticated encryption (AE) can help to encrypt the data before it is being transmitted to the network and is suitable for the resource-constrained platforms like FPGA, which can be used for IoT applications. In addition, AE can also provide the authenticity check of the data. Among many AE schemes, Ascon is a promising candidate currently under review by the U.S. National Institute of Standards and Technology (NIST) as a lightweight cryptography standard. This paper evaluates the performance of Ascon on various FPGA platforms. A recursive implementation strategy has been adopted to synchronize the clock cycles consumption and the number of permutations executed, which reduces the area consumption required for IoT applications. The proposed implementation is evaluated on various widely used FPGA platforms to showcase the performance of Ascon under various IoT application scenarios.