Security, privacy and trust: privacy preserving model for internet of things. (25th August 2020)

• Record Type: Journal Article
• Authors: Jain, Shelendra Kumar; Kesswani, Nishtha; Agarwal, Basant
• Is Part Of: International journal of intelligent information and database systems. Volume 13:Number 2/4(2020)
• Page Start: 249
• Page End: 277
• Publication Date: 2020-08-25
• Subjects: internet of things -- IoT -- data privacy protection -- obfuscation -- information privacy -- user privacy preservation -- trust -- healthcare; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Internet of things (IoT) has emerged as one of the dominant technologies. The IoT systems provide significant number of opportunities in solving many real-time problems such as in healthcare, transport, smart cities, etc. However, ensuring privacy protection is challenging as sensitive and personal information is communicated through the IoT devices. In this paper, we propose a privacy preserving model called as security, privacy and trust (SPT) that ensures data privacy in IoT devices through lightweight data collection and data access protocols in resource constrained IoT ecosystem. We have conducted the experiments on small scale dataset (1, 000 data points) and large scale dataset (10, 000 data points). The experimental results show that in the proposed SPT model, there is an improvement of 3.63% for small scale dataset and 12.87% improvement for large scale dataset in terms of average effective time. We also provide a case study of the proposed approach on the healthcare-based IoT system.