Hybrid Authentification System of Face Mask Detection Using CNN-based on Lightweight Cryptography and Blockchain Technology

Imen Hagui, Amina Msolli, Noura Ben Henda, A. Helali, Fredj Hassen, R. Mghaieth, Thanh Phuong Nguyen
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Abstract

COVID-19 is currently wreaking havoc around the world. A severe acute respiratory pattern causes acute COVID-19 disease (SARS-CoV-2). Face masks have become very popular in our daily life. These face shields have raised concerns about the accuracy of facial recognition technology used to check hand/student attendance and unlock phones. Many companies use facial recognition as an identification system and have created internal databases to implement such a system. Security and authentication are critical in these situations, as an untrusted hostile device can compromise an IoT system. In this study, we proposed a new method based on a fusion algorithm that merges password and image features to increase the randomness and security of the pattern structure and developed a combination of cryptography and blockchain technology. This technique ensures that the image verification system is protected when accepting standards for confidentiality and security information by transferring the model from the Acess point to the destination.
基于轻量级密码和区块链技术的cnn人脸检测混合认证系统
当前,新冠肺炎疫情正在全球肆虐。严重的急性呼吸模式导致急性COVID-19疾病(SARS-CoV-2)。口罩在我们的日常生活中变得非常流行。这些面罩引发了人们对用于检查手部/学生出勤和解锁手机的面部识别技术准确性的担忧。许多公司使用面部识别作为一种识别系统,并创建了内部数据库来实现这种系统。在这些情况下,安全性和身份验证至关重要,因为不受信任的恶意设备可能会危及物联网系统。在本研究中,我们提出了一种基于融合算法的新方法,将密码和图像特征融合在一起,以增加模式结构的随机性和安全性,并开发了密码学和区块链技术的结合。该技术通过将模型从接入点传输到目的地,确保图像验证系统在接受机密性和安全信息标准时受到保护。
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