Publication

Abstract : The Quick Response (QR) code, a machine-readable optical label, is a pattern two-dimensional of black and white blocks. At present its applications extend to various domains, including message sharing and document authentication, etc. It can store critical and important information through the encryption of data. It can store essential information through the encryption of data. The increased utilization of QR codes also raises concerns regarding privacy and security issues related to the information they contain. This project explores the combination of mathematical methods in computing, including LU Decomposition and Principal Component Anal-ysis (PCA), to devise a robust encryption approach. LU Decomposition, a matrix factorization technique, disintegrates a matrix into lower and upper triangular matrices. On the other hand, PCA is a statistical procedure utilized for dimensionality reduction. The results highlight the effectiveness and efficiency of em-ploying LU Decomposition and PCA for encryption, reinforcing QR code security.