Secured Model for Internet of Things (IoT) to Monitor Smart Field Data with Integrated Real-Time Cloud Using Lightweight Cryptography

Abstract

Monitoring the farm field data parameters is one of the important criteria for farmers to keep track of the cultivations and its progress. Internet of Things (IoT) powered system can be implemented in the farm field, with the help of sensors to sense the data from the farm field in the Real-Time cloud. The data collected at the farm field can be accepted after proper authentication from the farmer. Because of heterogeneous and dynamic nature of IoT network, it poses a tremendous threat to security and privacy. Authentication is one of the IoT environment's most demanding security requirements, where users can straightforwardly get to data from any sort of gadgets; we need to implement a mutual authentication mechanism between user and the gadgets. This paper illustrates how the protection of the message stage is achieved in IoT associations and presents an algorithm to identify the right cryptographic algorithm based on the value of device parameters. Various cryptographic algorithms are also assessed which are appropriate for the task and also assesses the algorithm operation time when processing larger messages. Tests with respect to pre-defined measurements are conducted and the measurements are analyzed by comparing the outcomes. At the end of the paper, all outcomes and analyzes are deciphered.

KEYWORDS:

• Cloud technology
• Cryptography
• Firebase
• Hash code
• IoT security
• Security analysis

Additional information

Notes on contributors

Y. Justindhas

Y Justindhas received his MTech degree from the Department of Information Technology at Sathyabama University, Chennai, India. He is currently an assistant professor at Easwari Engineering College, Chennai, India. He is pursuing his PhD degree in School of Computing from Sathyabama Institute of Science and Technology. His current research interest includes internet of things, webservices, network security, and machine learning.

P. Jeyanthi

P Jeyanthi received her PhD degree from Sathyabama University, Chennai, India. She is currently an associate professor at Sathyabama Institute of Science and Technology, Chennai, India. Her research interest includes data mining, image retrieval, big data analytics, internet of things and machine learning. Email: [email protected]