A Secure Framework for Offline Digital Signature Generation and Verification

Abstract

Identity is fundamental and a prerequisite for every function; without a legitimate identity, any process can be falsified or manipulated. Today, identity theft and misuse are common due to the widespread use of insecure data storage and processing platforms. Data is typically stored centrally, making it more vulnerable to compromise. In this realm of securing digital identity, implementing robust authentication methods and stringent protection of personal information is critical. The main objective of this research is to enhance the security and privacy of digital identities through the integration of encrypted biometric data and personal information into visual representations, allowing secure authentication eliminating the need for constant connectivity to a centralized database A biometric system analyses a person's physical characteristics to ensure their authenticity. The proposed system uses biometric data to uniquely identify individuals offline, rather than depending primarily on electronic chips or online databases. The method involves a series of steps, including feature extraction, compression, and encryption, to create a secure and efficient system. The extracted biometric data along with personal information undergo encryption using AES and RSA is used for secure management of AES keys ensuring that only authorized persons can access the data. Subsequently, the encrypted biometric data is compressed using efficient algorithms to reduce data size while preserving integrity. Finally, the data is seamlessly embedded into QR code and Cryptograph (an indigenously developed pattern), serving as portable, tamper-resistant containers for personal information.