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http://dx.doi.org/10.14400/JDC.2020.18.10.233

A Key Management Technique Based on Topographic Information Considering IoT Information Errors in Cloud Environment  

Jeong, Yoon-Su (Dept. of Information Communication & Engineering, Mokwon University)
Choi, Jeong-hee (Division of Software Liberal Arts, Stokes College, Mokwon University)
Publication Information
Journal of Digital Convergence / v.18, no.10, 2020 , pp. 233-238 More about this Journal
Abstract
In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.
Keywords
Cloud; Internet of Things; terrain information; key management; deep learning; probability-based; clustering;
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