4th International ICST Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities

Research Article

Optimizing AES for Embedded Devices and Wireless Sensor Networks

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  • @INPROCEEDINGS{10.4108/tridentcom.2008.10409,
        author={Shammi Didla and Aaron Ault and Saurabh Bagchi},
        title={Optimizing AES for Embedded Devices and Wireless Sensor Networks},
        proceedings={4th International ICST Conference on Testbeds and Research Infrastructures for the Development of Networks \& Communities},
        proceedings_a={TRIDENTCOM},
        year={2010},
        month={5},
        keywords={AES encryption embedded optimizations secure sensor net- works CC2420 MSP430 Zigbee security},
        doi={10.4108/tridentcom.2008.10409}
    }
    
  • Shammi Didla
    Aaron Ault
    Saurabh Bagchi
    Year: 2010
    Optimizing AES for Embedded Devices and Wireless Sensor Networks
    TRIDENTCOM
    ICST
    DOI: 10.4108/tridentcom.2008.10409
Shammi Didla1,*, Aaron Ault1,*, Saurabh Bagchi1,*
  • 1: Center for Wireless Systems and Applications (CWSA) Purdue University, West Lafayette, IN 47906, USA
*Contact email: sdidla@purdue.edu, ault@purdue.edu, sbagchi@purdue.edu

Abstract

The increased need for security in embedded applications in recent years has prompted efforts to develop encryption algorithms capable of running on resource constrained systems. The inclusion of the Advanced Encryption Standard (AES) in the IEEE 802.15.4 Zigbee protocol has driven its widespread use in current embedded platforms. We propose an implementation of AES in a high-level language (C in this case) that is the first software-based solution for 16-bit microcontrollers capable of matching the communication rate of 250 kbps specified by the Zigbee protocol, while also minimizing RAM and ROM usage. We discuss a series of optimizations and their effects that lead to our final implementation achieving an encryption speed of 286 kbps, RAM usage of 260 bytes, and code size of 5160 bytes on the Texas Instruments MSP430 microprocessor. We also develop rigorous benchmark experiments to compare other AES implementations on a common platform, and show that our implementation outperforms the best available implementation by 85%.