Swetha Sindhe, Dept of CSE, Vasavi College of Engineering, Hyderabad, India
Sunil Chandolu, Dept of CSE, Vasavi College of Engineering, Hyderabad, India
Machine learning has been embraced generally to performance expectations and classification. Executing machine learning builds security dangers when the calculation procedure includes delicate information on preparing and testing calculations. We present a proposed framework to ensure Machine learning motors in IoT condition without altering inner Machine learning design. Our proposed framework is intended for secret wordless and disposed of the outsider in executing Machine learning exchanges. To assess our proposed framework, we direct exploratory with Machine learning exchanges on IoT load up and measure calculation time every exchange. The test results show that our proposed framework can address security issues on Machine learning calculation with low time utilization.
Machine Learning, CP-ABE, Pairing Encryption, Security System
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APA:
Sindhe, S., & Chandolu, S (2020). Machine Learning Mechanisms in Secure IoT Requisitions with Identity-Based Encryption. International Journal of Control and Automation (IJCA), ISSN: 2005-4297 (Print); 2207-6387 (Online), NADIA, 13(7), 1-10. doi: 10.33832/ijca.2020.13.7.01.
MLA:
Sindhe, Swetha, et al. “Machine Learning Mechanisms in Secure IoT Requisitions with Identity-Based Encryption.” International Journal of Control and Automation, ISSN: 2005-4297 (Print); 2207-6387 (Online), NADIA, vol. 13, no. 7, 2020, pp. 1-10. IJCA, http://article.nadiapub.com/IJCA/vol13_no7/1.html.
IEEE:
[1] S. Sindhe, and S. Chandolu, "Machine Learning Mechanisms in Secure IoT Requisitions with Identity-Based Encryption." International Journal of Control and Automation (IJCA), ISSN: 2005-4297 (Print); 2207-6387 (Online), NADIA, vol. 13, no. 7, pp. 1-10, July 2020.
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