Securing an Efficient Lightweight AES Accelerator

The Advanced Encryption Standard (AES) is generally regarded as one of the most popular cryptographic algorithms for ensuring data security. Typical lightweight implementations of the algorithm published in the literature focus on area and power optimization, while neglecting the performance. This paper presents a novel lightweight approach for the AES algorithm and considers both encryption and decryption. In terms of performance per unit area and performance per unit power, our 32-bit design outperforms the state-of-the-art by 1.69x and 1.27x, respectively. These improvements become even larger when implementing higher data-path designs, such as 64-bit or 128-bit designs. To enhance its resilience against side-channel attacks, we modified our design by adopting and further improving on the most recent countermeasure, i.e., Domain-Oriented Masking (DOM). The results demonstrate that our five-stage and eight-stage 1^st-order DOM SBOX designs achieve a reduction in area of 9.9% and 6.9% compared to the original proposed design, respectively.

I. Introduction

According to a study that was recently released in the World Economic Forum [1], malicious attacks were launched against 1.5 billion Internet of Things devices during the first half of 2021. The number of instances of data breaches increased by 15.1% as compared to the previous year. As a consequence of this, the security of the Internet of Things (IoT) has become of the utmost importance and can no longer be treated as an afterthought. This is particularly true when considering the anticipated yearly increase in adoption of those devices, which is expected to reach 43 billion in the year 2023 [2]. With respect to data protection, the Advanced Encryption Standard (AES) [3] is one of the algorithms that is most generally recognized and utilized today. It was first presented to the public by the National Institute of Standards and Technology (NIST) in the year 2001. AES is currently the primary encryption method for many applications, including cloud computing [4] and health care [5]. Traditional implementations of the AES use pipelining techniques in order to achieve a high throughput [6]–[8]. However, as these implementations consume a significant amount of memory and power, it is unfeasible to use them in IoT devices that are limited by area and battery capacity [9]. Therefore, implementations of AES should be area and power efficient, while simultaneously minimizing the impact on throughput to the greatest degree possible.