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Efficient Security Algorithm for Power-Constrained IoT Devices

delete2021-04-01
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OA
AI
J
Joseph N. Mamvong *
G
Gokop Goteng
B
Bo Zhou
Y
Yue Gao
DOI:10.1109/JIOT.2020.3033435delete
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摘要

摘要

En 中文
Internet-of-Things (IoT) devices characterized by low power and low processing capabilities do not exactly fit into the provision of existing security techniques due to their constrained nature. Classical security algorithms that are built on complex cryptographic functions often require a level of processing that low-power IoT devices are incapable to effectively achieve due to limited power and processing resources. Consequently, the option for constrained IoT devices lies in either developing new security schemes or modifying existing ones to be more suitable for constrained IoT devices. In this work, an efficient security algorithm for constrained IoT devices, based on the advanced encryption standard, is proposed. We present a cryptanalytic overview of the consequence of complexity reduction together with a supporting mathematical justification, and provisioned a secure element (ATECC608A) as a tradeoff. The ATECC608A doubles for authentication and guarding against implementation attacks on the associated IoT device (ARM Cortex M4 micro-processor) in line with our analysis. The software implementation of the efficient algorithm for constrained IoT devices shows up to 35% reduction in the time it takes to complete the encryption of a single block (16 B) of plain text, in comparison to the currently used standard AES-128 algorithm, and in comparison to current results in literature at 26.6%.
Keyword:
Internet of Things
Encryption
Standards
Complexity theory
Signal processing algorithms
Complexity
constrained IoT devices
encryption
Internet-of-Things (IoT) security
security algorithms

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
7.8W

机构

Q
Queen Mary University London
学者数:
2.0W
论文数: 1.5W
被引数: 327
U
university of london
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21.5W
论文数: 19.7W
被引数: 305
L
Liverpool John Moores University
学者数:
5.7K
论文数: 6.5K
被引数: 1.1W
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