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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/t7gkmtmosnchrobulekbrcvtfe" style="color: black;">International Journal of Advances in Scientific Research and Engineering</a>
This paper details the development of an access control mechanism based on fingerprint biometrics and mobile phone International Mobile Equipment Identity (IMEI) modalities for the industrial internet of thing (Industrial IoT) Critical Infrastructure (CI) protection. The idea behind this study is to harden physical security through human identification and authentication processes to Smart CI places such as buildings, military bases, hospitals, airports and other important infrastructure.<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.31695/ijasre.2020.33940">doi:10.31695/ijasre.2020.33940</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/psb34rqsjjbhdhths5ysstcluy">fatcat:psb34rqsjjbhdhths5ysstcluy</a> </span>
more »... print and mobile phone IMEI are very recognized and accepted identities hence used in police criminal investigation and legal community. Other uses of mobile phone identities include e-medicine, mobile banking, mobile money and remote machine operation. The main objective of this study is to develop a prototype application for authentication and identification of legitimate Industrial IoT human entities/objects based on the mentioned two identities as opposed to traditional knowledge (password, phrase or personal identification number (PIN) etc.,) and possession (token, smart card, identity card etc.,) based Access Control instruments. To achieve this, the study based on eXtreme programming methodology was conducted using visual studio 2010 on DotNet framework 4.0 with C# object oriented programming language. The backend database employed was MySQL open-source Relational database management system (RDMBS). The research produced a number of key results include the development of fingerprint biometric and mobile phone IMEI human identity security layers (modules) and many others. The developed prototype application performance was evaluated by enrolled some fingerprints, IMEI and captured related individual personal information. The result indicated 99.999% accuracy levels. In conclusion, the study shows that the integration of fingerprint and mobile phone IMEI identities in access control roles can improve the security of the Industrial IoT institution and alleviate problems associated with traditional identity authentication methods.
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