Implementation of an Authentication System based on Facial Recognition, Artificial Intelligence and Blockchain
Implementation of an Authentication System based on Facial Recognition, Artificial Intelligence and Blockchain |
||
 |
 |
|
| © 2024 by IJETT Journal | ||
| Volume-72 Issue-1 |
||
| Year of Publication : 2024 | ||
| Author : Grimaldo Sthiward Casaño Rivera, Marko Jair Arteaga Polo, Laberiano Andrade-Arenas |
||
| DOI : 10.14445/22315381/IJETT-V72I1P113 | ||
How to Cite?
Grimaldo Sthiward Casaño Rivera, Marko Jair Arteaga Polo, Laberiano Andrade-Arenas, "Implementation of an Authentication System based on Facial Recognition, Artificial Intelligence and Blockchain," International Journal of Engineering Trends and Technology, vol. 72, no. 1, pp. 130-140, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I1P113
Abstract
This study proposes the implementation of an innovative login system that uses facial recognition based on artificial intelligence and blockchain technology to guarantee the privacy and security of the data of customers of the company Dialyma. The aim is to replace manual access with traditional credentials with a more secure and efficient facial biometric method. For this, Python is used in the backend and libraries such as OpenCV and TensorFlow for facial recognition. The Reniec service, called "Face Biometric Web Service", is implemented for facial validation. Blockchain technology is used to store and protect personal data securely, ensuring their integrity and preventing possible attacks or manipulations. The implementation of this system offers greater security data privacy and improves the user experience, reducing the risks associated with passwords. The results support its effectiveness in protecting the personal data of users of Dialyma customers. This innovative solution contributes to the protection of sensitive data, improves user experience and strengthens confidence in the management of personal information in the business environment.
Keywords
Authentication, System, Facial recognition, Blockchain, Python.
References
[1] Ashish Basare, Darshan Bhojak, and Ramesh Solanki, “Biometric Authentication System,” International Journal for Research in Applied Science and Engineering Technology, vol. 11, no. 6, pp. 3232-3238, 2023.
[CrossRef] [Publisher Link]
[2] Lixiang Li et al., “A Review of Face Recognition Technology,” IEEE Access, vol. 8, pp. 139110–139120, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Sifatnur Rahman, Mahabur Rahman, and Mijanur Rahman, “Automated Student Attendance System Using Fingerprint Recognition,” Edelweiss Applied Science and Technology, vol. 2, no. 1, pp. 90–94, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Lara-Jacho Steven Bryan, Albarracín-Zambrano Luis Orlando, and Ponce-Ruiz Dionisio Vitalio, “Facial Recognition Prototype to Improve Student Attendance Control at UNIANDES, Quevedo,” Revista Arbitrada Interdisciplinaria Koinonía, vol. 5, no. 2, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[5] José L. Aznarte, Mariano Melendo Pardo, and Juan Manuel Lacruz López, “On the Use of Facial Recognition Technologies in University: The Uned Case,” RIED-Revista Iberoamericana de Educacion a Distancia, vol. 25, no. 1, pp. 261–277, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Antón Fructuoso Freire Montero, “Facial Recognition as a Crime Investigation and Prevention Instrument,” Anuario da Facultade de Dereito da Universidade da Coruña, vol. 26, pp. 64–88, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Sukesha Subhash Patil, and Y.L. Puranik, “Blockchain Technology,” International Journal of Trend in Scientific Research and Development, vol. 3, no. 4, pp. 573–574, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Om Pal et al., “Key Management for Blockchain Technology,” ICT Express, vol. 7, no. 1, pp. 76–80, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Thien Huynh-The et al., “Blockchain for the Metaverse: A Review,” Future Generation Computer Systems, vol. 143, pp. 401–419, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Eimad Abusham et al., “Facial Image Encryption for Secure Face Recognition System,” Electronics (Switzerland), vol. 12, no. 3, pp. 1- 26, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Enrique Lee Huamaní, and Lilian Ocares-Cunyarachi, “Use of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity,” International Journal of Emerging Technology and Advanced Engineering, vol. 11, no. 11, pp. 68-75, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Moreano Rojas, and Maldonado Lezama, “Access Control Using Facial Recognition,” Thesis, Universidad Ricardo Palma Facultad de Ingeniería, pp. 1-18, 2019.
[Publisher Link]
[13] Jose Carlos Bustamante, Ciro Rodriguez, and Doris Esenarro, “Real Time Facial Expression Recognition System Based on Deep Learning,” International Journal of Recent Technology and Engineering, vol. 8, no. 2S11, pp. 4047–4051, 2019.
[CrossRef] [Publisher Link]
[14] María Isabel Rojo-Rivas et al., “Kriper: A Blockchain Network with Permissioned Storage,” Future Generation Computer Systems, vol. 138, pp. 160-171, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Anirudha B. Shetty et al., “Facial Recognition Using Haar Cascade and LBP classifiers,” Global Transitions Proceedings, vol. 2, no. 2, pp. 330–335, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Taufik Hidayat, and Rahutomo Mahardiko, “A Systematic Literature Review Method on AES Algorithm for Data Sharing Encryption on Cloud Computing,” International Journal of Artificial Intelligence Research, vol. 4, no. 1, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Yelsy Jiany Allen Ramirez, Lorvick Kayton Tucker Knight, and Dexon Mckensy Sambola, “Facial Recognition System for Employee Entry and Exit Control,” Wani, no. 76, pp. 3-11, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Ingrid Angélica García Torres et al., “API for Attendance Control with Facial Recognition Using OpenCv.JS,” Revista Tecnológica Ciencia y Educación Edwards Deming, vol. 5, no. 1, 2021.
[Google Scholar] [Publisher Link]
[19] Qinying Yuan, “Research on Classroom Emotion Recognition Algorithm Based on Visual Emotion Classification,” Computational Intelligence and Neuroscience, vol. 2022, pp. 1-10, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] P. Raguraman et al., “Color Detection of RGB Images Using Python and OpenCv,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 7, no. 1, pp. 109–112, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[21] R. Sandesh et al., “Smart Door Lock/Unlock Using Raspberry Pi,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 6, no. 3, pp. 543–548, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Faishal Rahaman et al., “Design and Implementation of a Face Recognition Based Door Access Security System Using Raspberry Pi,” International Research Journal of Engineering and Technology (IRJET), vol. 8, no. 11, pp. 1705-1709, 2021.
[Google Scholar] [Publisher Link]
[23] Sarra Namane, and Imed Ben Dhaou, “Blockchain-Based Access Control Techniques for IoT Applications,” Electronics (Switzerland), vol. 11, no. 14, pp. 1-29, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Xu Xu, Zhou Ruan, and Lei Yang, “Facial Expression Recognition Based on Graph Neural Network,” 2020 IEEE 5th International Conference on Image, Vision and Computing (ICIVC), Beijing, China, pp. 211–214. 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Alejandro Boza-Chua et al., “Development of a Security System Based on Facial Recognition Oriented to the Management and Diversion of Criminal Attacks,” International Journal of Emerging Technology and Advanced Engineering, vol. 12, no. 2, pp. 48–54, 2022.
[CrossRef] [Publisher Link]
[26] Juan Carlos Suárez Macedo, Nestor Asbel Cayllahua Aquino, Pedro Huamaní Navarrete, “Practical Approach of Application the Deep Learning Toolbox by Matlab in the Facial Recognition of Students,” Proceedings of the 18th Latin American and Caribbean Consortium of Engineering Institutions International Multi-Conference for Engineering, Education and Technology, pp. 1-9, 2020.
[CrossRef] [Publisher Link]
[27] R. Sivapriyan, N. Pavan Kumar, and H.L. Suresh, “Analysis of Facial Recognition Techniques,” Materials Today Proceedings, vol. 57, pp. 2350–2354, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Asma Akhtar, Birra Bakhtawar, and Samia Akhtar, “Extreme Programming Vs Scrum: A Comparison of Agile Models,” International Journal of Technology, Innovation and Management (IJTIM), vol. 2, no. 2, pp. 80-96, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Khusbhu Sahendrasingh Yadav, Maleeha Arif Yasvi, and Shubhika, “Review On Extreme Programming-XP,” International Conference on Robotics, Smart Technology Communication and Electronics Engineering, at Delhi, 2019.
[Google Scholar] [Publisher Link]
[30] Freddy Adrian Moreira Pinargote et al., “Methodological Proposal for Software Development in Degree Projects in the Specialty of Computer Systems Engineering,” IJERI: International Journal of Educational Research and Innovation, no. 12, pp. 76–89, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[31] E. Bautista, “Agile Methodologies XP and Scrum, Used for the Development of Web Pages, under MVC, with PHP Language and Laravel Framework,” 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[32] Alicia Raeburn, “Extreme Programming (XP) Produces Results, but is it the Right Methodology for you? Asana, Agile Methodology, 2022.
[Google Scholar] [Publisher Link]
[33] Alejandro Boza-Chua et al., “Development of a Security System Based on Facial Recognition Oriented to the Management and Diversion of Criminal Attacks,” International Journal of Emerging Technology and Advanced Engineering, vol. 12, no. 2, pp. 48–54, 2022.
[CrossRef] [Publisher Link]
[34] Jean Carlos Albuquerque Souza, and Marcus Rogério Oliveira, “Agile Methodologies: A Comparison between Extreme Programming (XP) and Scrum,” Ciência & Tecnologia, vol. 13, no. 1, pp. 133–141, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Diego León Ramírez-Bedoya, John Willian Branch-Bedoya, and Jovani Alberto Jiménez-Builes, “Methodology of Software Development for Robotic Educational Platforms Using ROS-XP,” Revista Politécnica, vol. 15, no. 30, pp. 55–69, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[36] Holman A. Montiel, Fredy S. Martínez, and Edwar G. Jacinto, “Implementation of Password Hashing on Embedded Systems with Cryptographic Acceleration Unit,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 2, 2022.
[CrossRef] [Google Scholar] [Publisher Link]