Today, protecting data privacy is considered as the most important challenge in the Internet of Things networks. These networks contain important data which is transmitted among the nodes. For this reason, it is very important to pay attention to the concern of data privacy in the Internet of Things. Studies show that the lack of a complete, efficient and standard model has caused many security flaws in these networks. By using the Internet limitations, this study discusses how to create a target function to protect data privacy in the Internet of Things. The proposed approach aims to find an optimal path with high competence. This method has been implemented in MATLAB software and the results of experiments show that although the Artificial Immune System (AIS) algorithm has no certain solution for optimization problems, it finds a near optimal answer. In addition, the response time of AIS algorithm is lower compared with the examined algorithms. According to the convergence diagrams, the AIS algorithm has good convergence.
Faridi Masouleh, M., harounabadi, A., & sayyad, A. (2022). Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations. Engineering Management and Soft Computing, 8(1), 123-151. doi: 10.22091/jemsc.2019.1297
MLA
Marzieh Faridi Masouleh; ali harounabadi; asal sayyad. "Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations". Engineering Management and Soft Computing, 8, 1, 2022, 123-151. doi: 10.22091/jemsc.2019.1297
HARVARD
Faridi Masouleh, M., harounabadi, A., sayyad, A. (2022). 'Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations', Engineering Management and Soft Computing, 8(1), pp. 123-151. doi: 10.22091/jemsc.2019.1297
VANCOUVER
Faridi Masouleh, M., harounabadi, A., sayyad, A. Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations. Engineering Management and Soft Computing, 2022; 8(1): 123-151. doi: 10.22091/jemsc.2019.1297
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