Verification of Peruvian Identity Document Fraud Through OCR, Hash Algorithm, and Simulated Blockchain Database

Nowadays, especially due to the COVID-19 pandemic, many professional, academic, and governmental operations have transitioned to digital environments. However, this poses the challenge of converting a large amount of documentation into digital format, which presents a high degree of vulnerability, especially in Peru. One of the documents most susceptible to cyber fraud and identity theft is the National Identity Document (DNI). This work focuses on verifying the validity of these documents using technologies such as Optical Character Recognition (OCR), in particular, the performance of two OCR options, EasyOCR and TesseractOCR, is evaluated. The proposed methodology involves obtaining a digital copy of the ID by scanning it with a printer, using both OCR techniques, and comparing their performance to determine which one yields better results. Then, the SHA-512 encryption algorithm is applied, and a hash is generated using the personal information extracted from the ID. Finally, the generated hash code undergoes a comparison with the stored hash derived from authentic data in a simulated blockchain database. This process serves to verify the genuineness and integrity of the original document. The results obtained demonstrate a satisfactory level of accuracy for the selected OCR, and the system effectively works to detect the authenticity of IDs, distinguishing between valid and fraudulent ones.