Measuring the performance and energy consumption of AES in wireless sensor networks

Panait, Cristina; Dragomir, Dan

doi:10.15439/2015f322

Cited by 20 publications

(8 citation statements)

References 12 publications

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“…The current sensing resistors used in the research by Lee et al [30] and Panait et al [31], differ from the one employed in this research being (1Ω). Lee et al [30] and Panait et al [31] make use of 10.1Ω and 4.99Ω resistors respectively. In addition to this, Panait et al [31] test the energy consumption of only AES implementations in different modes of operations.…”

Section: Previous Workmentioning

confidence: 90%

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Security and Performance in IoT: A Balancing Act

et al. 2020

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With predictions suggesting there will be 18 billion Internet of Things (IoT) devices live by 2022, performance of these low powered devices, as well as security is of utmost importance. Managing security and performance is a balancing act. Achieving this balance will always continue to be a challenge. This research presents two main contributions to this area. The first contribution is a framework to measure cryptographic performance of IoT devices. The areas of measurement are power consumption, time cost, energy cost, random access memory (RAM) usage and flash usage. The second contribution is an insightful comparison of the performance of the ATmega328, STM32F103C8T6 and ESP8266 low powered microcontroller devices. Experiments were conducted on these devices running various cryptographic operations. The measured operations are from three encryption algorithms: Advanced Encryption Standard (AES), ChaCha and Acorn. The proposed methods from this research are real-world in nature rather than simulated, and can be used by others wishing to conduct their own IoT performance testing. The results show that the ATmega328 has the lowest overall power consumption. The ESP8266 was generally the fastest performing device. ChaCha outperformed AES in both time cost and energy cost. Both algorithms outperformed Acorn in these metrics. The STM32F103C8T6 device displayed the best overall energy cost, while still performing well in terms of time. The results from the experiments conducted in this study can be used by network designers, developers and others to make appropriate decisions in IoT deployments with regards to balancing performance and security.

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Section: Previous Workmentioning

confidence: 90%

“…In this research a much smaller resistance is used for the current sensing resistor to ensure less wasted power, striving for a higher precision result. Panait et al [31] Panait et al measure a device based on the ATmega128RFA1 microcontroller. They conduct measurements on current and execution time of AES in ECB, CBC, CFB and CTR modes.…”

Section: Previous Workmentioning

confidence: 99%

Security and Performance in IoT: A Balancing Act

et al. 2020

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“…Result have shown that on encrypting data, hardware implementation of AES is the fastest; further in the work of [19] and [20], the result shows that hardware implementation of AES has a better throughput and more energy efficient. Similarly in the work of [21], when compared to AES software implementation it was justified by the result of their experiment that AES hardware implementation has lesser energy consumption and performs faster.…”

Section: Related Literaturementioning

confidence: 99%

Performance Evaluation of Lightweight Advanced Encryption Standard Hardware Implementation

Acla¹,

Gerardo²

2019

IJRTE

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 Abstract: Advanced Encryption Standard (AES) is one of the most secured encryption algorithm because of its robustness and complexity. Because of its complexity, AES has slow computation. This paper presents a Lightweight Advanced Encryption Standard (LAES) design by replacing the MixColumn transformation of the traditional AES with a 128-bit permutation to lessen its computational complexity. Implementation of hardware cryptographic encryption aims to find the best trade-off between throughput and resource utilization. The proposed design is synthesized on various Field Programmable Gate Array (FPGA) devices and achieves the maximum clock frequency of 480.50 MHz with the highest throughput of 6.15 Gbps when synthesized on Virtex 7 XC7VX690T. The results on other devices show a higher throughput, better performance efficiency, and lesser area utilization when compared to the existing AES hardware implementation.

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“…A sensor device using the MICAz with 4 KB RAM (Crossbow Technology, San Jose, CA, USA) and 7-MHz ATmega128L microcontroller (Microchip Technology Inc, Chandler, AZ, USA) and a smart phone using an iPhone 6s (Apple, Cupertino, CA, USA) with 2 GB RAM ARM (armv8-a) CPU. The data are taken from [13,24,25] for the time required on the MICAz while we implement those implementations on a smart phone using the Pairing Based Cryptographic Library [26]. The result is summarized in Table 2.…”

Section: C1mentioning

confidence: 99%

An Anonymous Mutual Authenticated Key Agreement Scheme for Wearable Sensors in Wireless Body Area Networks

Chen

Xiang

et al. 2018

Applied Sciences

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Abstract:The advancement of Wireless Body Area Networks (WBAN) have led to significant progress in medical and health care systems. However, such networks still suffer from major security and privacy threats, especially for the data collected in medical or health care applications. Lack of security and existence of anonymous communication in WBAN brings about the operation failure of these networks. Recently, Li et al. proposed a lightweight protocol for wearable sensors in wireless body area networks. In their paper, the authors claimed that the protocol may provide anonymous mutual authentication and resist against various types of attacks. This study shows that such a protocol is still vulnerable to three types of attacks, i.e., the offline identity guessing attack, the sensor node impersonation attack and the hub node spoofing attack. We then present a secure scheme that addresses these problems, and retains similar efficiency in wireless sensors nodes and mobile phones.

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Measuring the performance and energy consumption of AES in wireless sensor networks

Cited by 20 publications

References 12 publications

Security and Performance in IoT: A Balancing Act

Security and Performance in IoT: A Balancing Act

Performance Evaluation of Lightweight Advanced Encryption Standard Hardware Implementation

An Anonymous Mutual Authenticated Key Agreement Scheme for Wearable Sensors in Wireless Body Area Networks

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