The Improvement of the Iris-Based Authentication by Presenting the Wireless Sensor Network Architecture to Maintain Industrial Internet of Things Privacy
1
Department of Computer Science, Faculty of Mathematics and Computer Science, Kharazmi University, Tehran, Iran
2
Faculty of Management, Kharazmi University
Abstract
The Internet of Things provides instant access to information about the physical world and the objects within it, leading to new services and increasing efficiency and productivity. The wireless sensor network is an important network infrastructure in the Industrial Internet of Things and user authentication is used as a basic security mechanism to authenticate users to wireless sensor networks. In this article, we intend to provide a new way to improve the security of authentication using image processing. The analysis was performed by MATLAB software. The results presented in this article, which includes seven steps, have a 93% correct detection rate in pupil identification. These seven steps are: 1. Noise reduction, 2. Finding the outer border of the pupil, 3. Separating the eyelashes, 4. Finding the border of the eyelids, 5. Finding the outer border of the iris, 6. Separating the iris area and 7. Extracting the feature and encoding the pixels by the elliptic curve cryptography (ECC) method. With the measurements and experiments performed, it was found that the proposed method in identifying the eyelid border by the quadratic equation method is more efficient and faster in terms of time than the third-degree equation and the Huff parabolic conversion method. In order to extract the feature, the effective parameters in the SAIF feature extraction algorithm were examined and measured, and the optimal parameters were selected. The Sigma parameter with a value of 2.5 and the Octave parameter with a value of 4 should be considered as the best values. Also, in order to evaluate the resistance of the proposed method to error factors such as the angle, brightness and scale, the proposed method was tested and it was proved that the method has the appropriate resistance resolution in different conditions.
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Borna, K., Ebadati, O. M., & Zeynali, S. (2021). The Improvement of the Iris-Based Authentication by Presenting the Wireless Sensor Network Architecture to Maintain Industrial Internet of Things Privacy. , 1(4), 35-50.
MLA
Keivan Borna; Omid Mahdi Ebadati; Shayan Zeynali. "The Improvement of the Iris-Based Authentication by Presenting the Wireless Sensor Network Architecture to Maintain Industrial Internet of Things Privacy", , 1, 4, 2021, 35-50.
HARVARD
Borna, K., Ebadati, O. M., Zeynali, S. (2021). 'The Improvement of the Iris-Based Authentication by Presenting the Wireless Sensor Network Architecture to Maintain Industrial Internet of Things Privacy', , 1(4), pp. 35-50.
VANCOUVER
Borna, K., Ebadati, O. M., Zeynali, S. The Improvement of the Iris-Based Authentication by Presenting the Wireless Sensor Network Architecture to Maintain Industrial Internet of Things Privacy. , 2021; 1(4): 35-50.
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