Palmprint Recognition Using AES Algorithm with Machine Learning

In recent years, data security and data privacy have become increasingly critical. The data can be divided into two categories: public data, which is accessible to anybody, and private data, which is only accessible to users. Both UIDAI data in transit and data at rest are vulnerable. To secure Aadhaar data, an effective encryption solution must be employed. This study presents a way for securing a dataset against assaults by combining cryptographic secure technique with biometric authentication. The research technique is divided into two modules: cryptography and biometrics. The cryptography section uses the Advanced Encryption Standard (AES) algorithm, while the biometrics section uses the palmprint recognition method. AES is a symmetric data encryption scheme since it encrypts and decrypts data using a single, randomly generated key. Palmprint recognition is one of the most common methods for identifying and verifying authorized users. For palmprint-based authentication, a specialized convolutional neural network (CNN) model is constructed, trained, and then used as a verification mechanism. Various findings that demonstrate that the method is a good choice are discussed in this work.