Behavioral Biometrics Are Based On A Person's Actions ✓ Solved

300 Wordsbehavioral Biometrics Are Based Upon A Persons Actions Or Me

Behavioral biometrics are based upon a person’s actions or measurements of body movement. Respond to the following: Select from one of the following lower or newer behavioral metrics: Facial recognition Signature analysis Gait analysis Keystroke analysis Explain how your selected biometric works. What are the ways that it be used in criminal investigations? Explain the limitations of your selected biometric. When reviewing 2 other student responses, choose a different biometric.

Sample Paper For Above instruction

Behavioral biometrics have emerged as significant tools in the field of security and criminal investigations, providing a dynamic method of identifying individuals based on unique behavioral patterns. Among these, gait analysis has gained prominence due to its non-intrusive nature and the ability to analyze individuals from a distance. Gait analysis refers to the study of how a person walks, leveraging the unique patterns in their stride and movement to establish identity. This biometric works by capturing video footage or sensor data, then extracting features such as stride length, cadence, limb movement, and posture. Advanced algorithms process this information to create a gait profile that can be compared against existing profiles for verification or identification purposes (Nanni et al., 2018).

In criminal investigations, gait analysis can be instrumental in tracking suspects without their knowledge, especially in outdoor environments where traditional security measures are insufficient. For instance, surveillance footage from a distance can reveal the gait pattern of an individual, which can be matched with previous recordings or databases. Gait analysis has also been used successfully in identifying perpetrators involved in crimes such as theft or assault, where physical evidence might be limited. Its ability to function in real-time makes it a powerful adjunct to other biometric modalities like facial recognition (Ahmed & Al-Mujaini, 2020).

Nevertheless, gait analysis has inherent limitations. Variations in clothing, footwear, and surface conditions can alter gait patterns, leading to false negatives or positives. Additionally, gait can be intentionally disguised or mimicked, reducing system reliability. Physical injuries or changes in health might also affect gait, causing inaccuracies over time. Environmental factors such as poor lighting or camera angles further constrain its effectiveness. Therefore, while gait analysis is promising, it is most effective when integrated with other biometric measures to improve accuracy and robustness (Kong et al., 2019).

References

  • Nanni, L., Lumini, A., & Brahnam, S. (2018). Gait recognition: A comprehensive review. Pattern Recognition Letters, 106, 98-107.
  • Ahmed, M., & Al-Mujaini, A. (2020). Surveillance and gait analysis for biometric identification. Journal of Forensic Sciences, 65(5), 1478-1486.
  • Kong, B., Liu, S., & Zhou, J. (2019). Limitations of gait biometric systems in real-world scenarios. IEEE Transactions on Biometrics, 11(3), 123-134.
  • Guan, J., & Wang, Y. (2017). Advances in gait recognition techniques. Computer Vision and Image Understanding, 154, 83-91.
  • Zhao, R., & Kumar, R. (2019). Ethical considerations in behavioral biometric systems. Ethics and Information Technology, 21(1), 37-45.
  • Li, X., & Chen, Z. (2021). Multi-modal biometric identification: Current trends and challenges. IEEE Transactions on Cybernetics, 51(4), 2022-2032.
  • Patel, D., & Sinha, A. (2020). The role of gait analysis in forensic investigations. Forensic Science International, 311, 110313.
  • Song, Q., & Zhang, H. (2017). Environmental impacts on biometric recognition accuracy. Journal of Pattern Recognition Research, 12(2), 109-121.
  • El-Bakry, H., & Abdelrahman, E. (2019). Security risks and limitations of behavioral biometrics. International Journal of Security and Networks, 14(3), 145-154.
  • Wang, L., & Song, J. (2022). Improving biometric systems with multi-factor authentication. Journal of Information Security, 13(3), 112-125.

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