IoT-Centric Data Protection Using Deep Learning Technique for Preserving Security and Privacy in Cloud

J. Abitha, R. Sadhana

doi:https://doi.org/10.59232/DSM-V1I1P104

Research Article | Open Access | Download Full Text

Volume 1 | Issue 1 | Year 2024 | Article Id: DSM-V1I1P104 DOI: https://doi.org/10.59232/DSM-V1I1P104

IoT-Centric Data Protection Using Deep Learning Technique for Preserving Security and Privacy in Cloud

J. Abitha, R. Sadhana

Received	Revised	Accepted	Published
21 Oct 2023	20 Nov 2023	13 Dec 2023	22 Jan 2024

Citation

J. Abitha, R. Sadhana. “IoT-Centric Data Protection Using Deep Learning Technique for Preserving Security and Privacy in Cloud.” DS Journal of Multidisciplinary, vol. 1, no. 1, pp. 23-30, 2024.

Abstract

A system of interconnected, the Internet of Things (IoT) is a term that refers to physical objects that may be connected online. Concerns over user privacy on the Internet of Things are growing as a result of the large amounts of personal data being gathered and exchanged there. IoT devices may increase productivity, accuracy, and financial gain in addition to reducing human intrusion, giving Internet of Things applications the most flexibility and convenience. Overhead of communications, security, and privacy, IoT is experiencing issues as well. As a result, protecting data has grown to be a difficult undertaking that must be handled carefully. This study offers a secure data security solution for preserving privacy in the cloud environment to address this crucial and difficult topic. It does this by efficiently separating the data by separating sensitive data from non-sensitive data with an SVM classifier and then using the data to partially decrypt and analyze, which increases the effectiveness of the model while ensuring security. The sensitive data was protected using Okamato Uchiyama encryption. The model safely stores, analyzes, and shares data to ensure the system’s safety and privacy. The novel method was compared to existing methodologies regarding particular parameters like precision, accuracy, F1 score, and recall.

Keywords

Cloud computing, Internet of Things, Support Vector Machine, Okamato Uchiyama.

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