4.3 Article

A low cost fault-attack resilient AES for IoT applications

Journal

MICROELECTRONICS RELIABILITY
Volume 123, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.microrel.2021.114202

Keywords

Advanced encryption standard (AES); Error detection; Internet-of-things (IoTs); Compact implementation; Fault-attack resiliency

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The Internet of Things plays a crucial role in various domains, but its security remains a challenge. To address security concerns, this paper proposes a 32-bit architecture AES encryption/decryption scheme and a fault-resilient integrated architecture named LC-FRAES to ensure communication reliability and security.
The Internet of Things (IoT) as an emerging infrastructure has an essential rule in daily lives in many domains, ranging from healthcare wearable devices to complex industrial systems. Nevertheless, its security is a challenging issue that has to be addressed. The security can be settled by utilizing cryptographic techniques such as Advanced Encryption Standard (AES) for encryption and authentication. In this paper, we propose 32-bit architecture AES encryption/decryption for utilizing in IoT infrastructure and similar resource-constrained applications. On the other hand, providing robustness against existing malicious attacks is a significant factor in ensuring communication reliably and so securely. Therefore, we propose a low-cost fault-resilient integrated architecture, named LC-FRAES, for data-path and also on-the-fly key expansion unit by exploiting of resource sharing between encryption and decryption processes. The results of both ASIC and FPGA implementations of the proposed architecture are reported and also compared with those of similar recent designs. The comparisons illustrate that the LC-FRAES outperforms its counterparts in many architectural features which make it suitable for IoT applications. Moreover, we provide a comparison between our proposal and lightweight cryptographic designs from literature. The comparisons verify the consistency and appropriateness of proposed architecture for IoT applications. Finally, through the extensive experimental results, we show that LC-FRAES can detect almost all injected faults.

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