Back to Search
Start Over
AgriTrust-A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things.
- Source :
-
Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Oct 29; Vol. 20 (21). Date of Electronic Publication: 2020 Oct 29. - Publication Year :
- 2020
-
Abstract
- Internet of Things (IoT) provides a diverse platform to automate things where smart agriculture is one of the most promising concepts in the field of Internet of Agriculture Things (IoAT). Due to the requirements of more processing power for computations and predictions, the concept of Cloud-based smart agriculture is proposed for autonomic systems. This is where digital innovation and technology helps to improve the quality of life in the area of urbanization expansion. For the integration of cloud in smart agriculture, the system is shown to have security and privacy challenges, and most significantly, the identification of malicious and compromised nodes along with a secure transmission of information between sensors, cloud, and base station (BS). The identification of malicious and compromised node among soil sensors communicating with the BS is a notable challenge in the BS to cloud communications. The trust management mechanism is proposed as one of the solutions providing a lightweight approach to identify these nodes. In this article, we have proposed a novel trust management mechanism to identify malicious and compromised nodes by utilizing trust parameters. The trust mechanism is an event-driven process that computes trust based on the pre-defined time interval and utilizes the previous trust degree to develop an absolute trust degree. The system also maintains the trust degree of a BS and cloud service providers using distinct approaches. We have also performed extensive simulations to evaluate the performance of the proposed mechanism against several potential attacks. In addition, this research helps to create friendlier environments and efficient agricultural productions for the migration of people to the cities.
Details
- Language :
- English
- ISSN :
- 1424-8220
- Volume :
- 20
- Issue :
- 21
- Database :
- MEDLINE
- Journal :
- Sensors (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 33138295
- Full Text :
- https://doi.org/10.3390/s20216174