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It is very convenient and secure since it compares the user\u2019s own biometrics with those stored in the database to confirm their identification. Since then, with the vigorous development of machine learning, the performance and accuracy of biometric authentication have been greatly improved. Face recognition technology combined with convolutional neural network (CNN) is extremely efficient and has become the mainstream of access control systems (ACSs). However, identity information and access logs stored in traditional databases can be tampered by malicious insiders. Therefore, we propose a face recognition ACS that is resistant to data forgery. In this paper, a deep convolutional network is utilized to learn Euclidean embedding (based on FaceNet) of each image and achieve face recognition and verification. Quorum, which is built on the Ethereum blockchain, is used to store facial feature vectors and login information. Smart contracts are made to automatically put data into blocks on the chain. One is used to store feature vectors, and the other to record the arrival and departure times of employees. By combining these cutting\u2010edge technologies, an intelligent and immutable ACS that can withstand distributed denial\u2010of\u2010service (DDoS) and other internal and external attacks is created. Finally, an experiment is conducted to assess the effectiveness of the proposed system to demonstrate its practicality.<\/jats:p>","DOI":"10.1049\/ise2\/6755170","type":"journal-article","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T02:22:30Z","timestamp":1741573350000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BF\u2010ACS\u2014Intelligent and Immutable Face Recognition Access Control System"],"prefix":"10.1049","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8874-8448","authenticated-orcid":false,"given":"Wen-Bin","family":"Hsieh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"265","published-online":{"date-parts":[[2025,3,3]]},"reference":[{"key":"e_1_2_12_1_2","unstructured":"IEEE Standards Association IEEE 2945-2023 IEEE Standard for Technical Requirements for Face Recognition 2023."},{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"e_1_2_12_3_2","doi-asserted-by":"crossref","unstructured":"AloysiusN.andGeethaM. 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