As a digitalization of attendance systems and identity authentication systems at places like factories, airports, educational institutions, healthcare centers, etc. They contain a lot of biometric data like fingerprints, so there is a high risk of data breaches from the databases used by the authentication centers. The biometrics are less costly to upkeep, so it is very economical. The biometric data is susceptible, and sometimes attackers may use it to cause financial damage using these biometric data, as they are used in many government identity cards as proof. Due to this, it becomes essential to protect these data. Research communities have proposed many image security solutions to prevent security breaches. Unfortunately, many cryptosystems today have excessive computational complexity and inadequate security. Thus, protecting these biometric image data and lowering computing complexity are the primary goals of our work. So we have proposed an encryption technique which contain dual confusion followed by a diffusion process. For the first part of confusion, we have designed a divide-rotate algorithm and for the second phase, we have developed a pixel shifting algorithm. A pseudo-random sequence generator is used to generate a chaotic range of values and diffuse the image, and in this process, a Logistic map is used. Studies on security and performance show that the suggested approach has a high degree of randomness and is resistant to statistical entropy-based, differential as well as brute-force attacks. From the analysis and findings, it is clear that the suggested method is incredibly sensitive, financially trustworthy, and performs better than other similar state-of-the-art systems, all with reduced computing complexity. 

Highlights

• Using a chaotic map, protect the biometric data against financial fraud.
• In order to protect the fingerprint data financially, an encryption technology has been developed.