Biometric Authentication Methods in The Data Systems

Biometric authentication is form of access control that gives access permission to individuals based on verification using their physical features which are previously recorded on a scanner or a biometric security system (Lazkani & Liu, 2014). During the process of biometric authentication, the system makes a comparison between two sets of data: information recorded in the system and the one provided by the visitor. Permission is only granted if the device confirms that the two data sets are identical or nearly identical.

The most common biometric authentication methods include fingerprint affirmation, face recognition, retina and iris, and voice recognition. The method of biometric authentication is used by both big and small organizations to control access to systems in the contemporary world (Pato, Millett, & Lynette, 2010). Despite the technology of biometric authentication gaining popularity in the recent past, the method has some weaknesses. One of the main problems with this method is the procedure used to capture and map the physical features to an individual.

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The process requires high levels of accuracy and precision when capturing the details. Lack of accuracy or taking incomplete data will lead to failure of the whole system.

Another limitation is that biometrics are permanent for a lifetime. Any other form of authentication such as passwords can be changed by a user when need arises or when someone else learns about them. However, there is no means through which one can change their biometrics such as the retina, fingerprints and iris. In situations where a hacker gets a hold of these information, there is little that one can do to stay safe apart from changing the method of authentication or using another fingerprint.

In one of the biggest data breaches in history, hackers managed to get away with the fingerprints of more than 5.6 million employees of the Personal Management office. All the workers whose information was leaked will always have their identity compromised (Pato, Millett, & Lynette, 2010).

The third weakness entails errors in the biometric systems. The common errors include false accept and false reject. The errors usually occur because of a biometric device being unable to read the features of an individual due to several reasons. The false accept occurs when then system gives access to an unauthorized person while false reject is when the device fails to recognize an authorized individual. The system is not also applicable to the physically challenged. Apart from these weaknesses, the system has many other challenges. There are various controls which can be applied to overcome the challenges of biometric authentication.

One of the best methods used to correct the common privacy issues related to biometric authentication is the use of biometric template protection. The technique entails systems storing and transferring a changed version of the initial biometric features to avoid the adverse consequences of compromised databases and to protect peoples’ original data. Examples of biometric template protection methods include bio hashing and the use of cancellable biometrics. Cryptographic primitives could also be used to solve the problem of privacy in biometric authentication. The main cryptographic software used for such purposes include boom filters, secure multiparty computation and verifiable computation. Secure multiparty computation entails such techniques as oblivious transfer, garbled circuits and homomorphic encryption. The three techniques are usually combined to achieve privacy preservation (Pagnin & Mitrokotsa, 2017).

The last control is the use of error correction codes. The error correction codes are used to reduce the errors experienced biometric data capture and storage. The technique works by eliminating the small variations that occur in capturing the initial template of the biometrics. As a result, systems get templates that are free of errors and hence use cryptographic primitives without interrupting with the original templates (Pagnin & Mitrokotsa, 2017).

Works cited

1. Lazkani, M. K., & Liu, J. K. (2014). Biometric Authentication: A Review. Journal of Information Assurance and Security, 9(5), 226-234.
2. Pato, J., Millett, L. I., & Lynette, D. (2010). Security Issues in Biometric Systems: A Review. Information Security Journal: A Global Perspective, 19(5), 233-245.
3. Pagnin, E., & Mitrokotsa, A. (2017). Cryptographic Techniques for Privacy-Preserving Biometric Authentication: A Survey. Cryptography and Communications, 9(5), 707-738.
4. Jain, A. K., Ross, A., & Prabhakar, S. (2004). An Introduction to Biometric Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 4-20.
5. Ratha, N. K., Connell, J. H., & Bolle, R. M. (2001). Enhancing Security and Privacy in Biometrics-Based Authentication Systems. IBM Systems Journal, 40(3), 614-634.
6. Jain, A. K., Flynn, P., & Ross, A. (2007). Handbook of Biometrics. New York, NY: Springer.
7. Wayman, J. L., Jain, A. K., & Maltoni, D. (2005). An Introduction to Biometric Authentication Systems. In D. Maltoni, D. Maio, A. K. Jain, & S. Prabhakar (Eds.), Handbook of Fingerprint Recognition (pp. 1-22). New York, NY: Springer.
8. Jain, A. K., Bolle, R. M., & Pankanti, S. (1999). Biometrics: Personal Identification in Networked Society. Norwell, MA: Kluwer Academic Publishers.
9. Das, D. K., & Nandy, A. (2014). Biometric Authentication Systems: A Review. International Journal of Advanced Research in Computer Science and Software Engineering, 4(12), 852-857.
10. Dey, N., & Ashour, A. S. (2018). Biometric-Based Physical and Cybersecurity Systems. Boca Raton, FL: CRC Press.