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A secure IoT-based micro-payment protocol for wearable devices

delete2022-01-17
delete9
PRE
AI
S
Sriramulu Bojjagani *
P
P. V. Venkateswara Rao
D
Dinesh Reddy Vemula
B
B. Ramachandra Reddy
T
T. Jaya Lakshmi
DOI:10.1007/s12083-021-01242-ydelete
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摘要

摘要

En 中文
Wearable devices are parts of the essential cost of goods sold (COGS) in the wheel of the Internet of things (IoT), contributing to a potential impact in the finance and banking sectors. There is a need for lightweight cryptography mechanisms for IoT devices because these are resource constraints. This paper introduces a novel approach to an IoT-based micro-payment protocol in a wearable devices environment. This payment model uses an elliptic curve integrated encryption scheme (ECIES) to encrypt and decrypt the communicating messages between various entities. The proposed protocol allows the customer to buy the goods using a wearable device and send the mobile application's confidential payment information. The application creates a secure session between the customer, banks and merchant. The static security analysis and informal security methods indicate that the proposed protocol is withstanding the various security vulnerabilities involved in mobile payments. For logical verification of the correctness of security properties using the formal way of Burrows-Abadi-Needham (BAN) logic confirms the proposed protocol's accuracy. The practical simulation and validation using the Scyther and Tamarin tool ensure that the absence of security attacks of our proposed framework. Finally, the performance analysis based on cryptography features and computational overhead of related approaches specify that the proposed micro-payment protocol for wearable devices is secure and efficient.
Keyword:
Internet of things (IoT)
Wearable device
Mobile payments
ECIES
BAN logic
Scyther
Tamarin

期刊

Peer-to-Peer Networking and Applications 封面图
Peer-to-Peer Networking and Applications
IF:
2.6
论文数:
2.2K
被引数:
2.9K

机构

S
srm university-ap
学者数:
1.0K
论文数: 880
被引数: 0
M
Madanapalle Institute of Technology and Science
学者数:
329
论文数: 340
被引数: 10
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