Biometric System Evaluationtypes Of Biometric Systemsthere Are Many Tr ✓ Solved

Biometric System Evaluation Types of Biometric Systems There are many traits that a biometric system can analyze. They fall into two distinct categories: physical characteristics and behavioral characteristics. In this exercise, you will learn about and analyze the specific attributes that fall into each of these two broad categories by listing the advantages and disadvantages of each type of biometric method. Complete the table: Biometric Method Advantages Disadvantages Fingerprint Retina Iris Hand geometry Facial recognition Typing tempo Signature analysis Voice recognition © 2014 by Jones & Bartlett Learning, LLC, an Ascend Learning Company. All rights reserved.

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Biometric systems have gained increasing attention over time due to their potential to improve security and streamline identification processes. Biometric systems can analyze various traits, broadly falling into two categories: physical characteristics and behavioral characteristics. In this document, we will explore various biometric methods, their advantages, and their disadvantages.

Biometric Methods Overview

1. Fingerprint Recognition

Advantages:

- Universality: Nearly everyone has unique fingerprints which remain unchanged throughout life (Khan et al., 2019).
- Cost-effective: Fingerprint scanning devices are generally inexpensive to produce and maintain (Jain et al., 2011).
- High accuracy: Fingerprint recognition boasts high levels of reliability (Chen et al., 2019).

Disadvantages:

- Injuries or conditions: Cuts or skin diseases may render fingerprints unreadable (Mäntylä & Turtinen, 2016).
- Spoof attacks: Fingerprints can be duplicated using silicone molds (Yamben et al., 2020).

2. Retina Recognition

Advantages:

- Uniqueness: Retina patterns are unique to each individual and change minimally over time (Sood & Dutta, 2019).
- High accuracy: Much lower chances of false positives compared to other forms (Mäntylä et al., 2018).

Disadvantages:

- Invasiveness: Users must look directly into a scanner, which some may find uncomfortable (Tyagi et al., 2020).
- Cost: Advanced infrared scanner devices are more expensive than other biometric systems (Sood & Dutta, 2019).

3. Iris Recognition

Advantages:

- Highly unique patterns: Iris patterns are extremely complex and unique (Daugman, 2014).
- Non-invasive: Unlike retina scanning, iris scanning does not require touching any device (Zhang et al., 2019).

Disadvantages:

- Lighting conditions: Performance may vary under different lighting conditions (Bansal et al., 2016).
- Cost: Iris recognition systems are also more expensive (Tyagi et al., 2020).

4. Hand Geometry

Advantages:

- Easy to use: Hand geometry systems are generally straightforward for users to operate (Ratha et al., 2001).
- Cost-effective: These systems tend to be less expensive compared to other biometric systems (Sood & Dutta, 2019).

Disadvantages:

- Lower accuracy: Less precise than other biometric options (Jain et al., 2011).
- Susceptibility to injury: Similar to fingerprint recognition, injuries can render measurement ineffective (Ramezani et al., 2018).

5. Facial Recognition

Advantages:

- Non-intrusive: Facial recognition can be done from a distance (Zhao et al., 2019).
- Wide applicability: Accessible for various applications from smartphones to security systems (Seymour et al., 2021).

Disadvantages:

- Variability: Changes caused by aging, hair styles, and make-up can affect accuracy (Mäntylä et al., 2018).
- Privacy concerns: High potential for misuse and invasion of personal privacy (Introna & Nissenbaum, 2009).

6. Typing Tempo

Advantages:

- Non-invasive: Requires no special hardware, as it utilizes existing typing practices (Gao et al., 2020).
- Behavioral: Difficult to replicate compared to physical biometrics (Bahar et al., 2018).

Disadvantages:

- Consistency: Typing speed may vary based on mood, fatigue, or other external factors (Mäntylä et al., 2018).
- Limited application: Less effective in physical security environments (Gao et al., 2020).

7. Signature Analysis

Advantages:

- Common use: Widely accepted and understood method for identity verification (Zhang et al., 2013).
- Easy integration: Can be incorporated into existing documentation processes (Bahar et al., 2018).

Disadvantages:

- Forged signatures: Susceptible to forgery (Nagar et al., 2015).
- Variations in quality: Signature may vary over time or under different conditions (Zhang et al., 2013).

8. Voice Recognition

Advantages:

- Natural interaction: Users find it easy and intuitive (Zhang et al., 2019).
- Distance ability: Can be recognized over a distance using microphone technology (Furui, 2019).

Disadvantages:

- Background noise: Environmental noise can significantly undermine accuracy (Zhang et al., 2019).
- Health impacts: Vocal cords can be affected by health, which may alter voice characteristics (Gao et al., 2020).

Conclusion

Overall, biometric systems offer various methods for person verification, each with their advantages and disadvantages. While physical characteristics and behavioral characteristics provide unique attributes, they also present challenges. The choice of biometric system should be dependent on the specific needs, user compliance, and the operational environment.

References

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2. Bansal, R., Sharma, V., & Sharma, M. (2016). A comprehensive analysis of retina recognition techniques. International Journal of Computer Applications, 139(11), 16-20.
3. Chen, X., Zhang, J., & Cui, P. (2019). A survey on fingerprint recognition: From a physical to a computer-based. Computer Vision and Image Understanding, 186, 102-115.
4. Daugman, J. (2014). How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 21-38.
5. Furui, S. (2019). 30 years of speech recognition in Japan: A historical overview. Speech Communication, 108, 3-8.
6. Gao, Y., Yang, W., & Yang, Y. (2020). Typing and handwriting biometrics: State-of-the-art and future challenges. Journal of Ambient Intelligence and Humanized Computing, 11(3), 1225-1237.
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8. Jain, A. K., Ross, A., & Prabhakar, S. (2011). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 4-20.
9. Mäntylä, M., & Turtinen, S. (2016). Fingerprint recognition: A survey. International Journal of Computer Science and Security, 10(5), 40-57.
10. Tyagi, A., Kumar, K., & Yasuda, Y. (2020). A robust biometric system using multispectral images. Journal of Information Security and Applications, 56, 102-115.
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