Implementation of authenticated encryption with associated data grain-128aead algorithm on stm32f400 processor family

  • Nhu Quynh Luc

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
  • Thi Nga Tran

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
  • Cong Khanh Ngo

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
  • Huy Duc Tran

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
  • Van Chien Nguyen

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
  • Tien Anh Tran

    Academy of Cryptography Techniques, 141 Chien Thang Road, Tan Trieu, Thanh Tri, Hanoi, Vietnam
Email: quynhln@actvn.edu.vn
Từ khóa: Light-weight cryptography, IoT security, stream ciphers, Grain-128AEAD algorithm.

Tóm tắt

An embedded device is becoming popular in daily life thanks to their low power consumption and multiprocessing capability. In particular, the security of embedded devices has been a big issue of concern to academic and industrial communities. This study aims at the Grain 128-AEAD authenticated encryption with associated data algorithm embedded on low-power and resource-constrained devices. This stream cipher belongs to the Grain family developed from the Grain-128a algorithm, and it has the advantage of not only providing security, but also adding authenticity to the associated data to ensure the authenticity, integrity and confidentiality of the data. It is also considered suitable for IoT (Internet of Thing) platforms and embedded device applications with limited resources and low power consumption. In this study, the algorithm was implemented on STM32 processor family. The resulting code size is only 832 bytes, and the total execution time for a 128-byte input block of Grain-128AEAD algorithm (Encryption and Decryption) takes 30 µs, which is better than previous implementations on various hardware platforms. The compiled file size is only 54kB, which makes the algorithm fit embedded applications.

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