Posted: July 26th, 2022

The Effectiveness of Biometrics

Evidence Evaluation Paper Draft
The Effectiveness of Biometrics
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Institutional Affiliation
Effectiveness of Biometrics Solutions
Biometric solutions have experienced an increased rate of development and adoption to improve security, convenience, and inclusion within society (Accenture, 2012). Amidst this increased rate of development and adoption of the new biometric technologies and the constant endorsement by various stakeholders, there are still legitimate concerns about its use, especially in the particular conception of security (Accenture, 2012). This evidence evaluation paper evaluates current evidence that points to the effectiveness of these solutions, especially in the security sector. Biometric technologies require a responsible deployment and utilization within the security realm to attain high-security levels.
Biometric systems do contain particular properties that have seen them adopted in numerous civilian and military applications. The biometric traits include an individual’s fingerprints, finger-veins, iris, voices, and face. In the law enforcement system, biometric technologies such as recognition systems have been adopted in many Western countries (Yang et al., 2019). The Department of Defense and the FBI implemented the Next-generation Identification (NGI) that would incorporate fingerprints, the face, iris, and palm information as part of their recognition programs. The systems have also been implemented in border control processes where they track and manage passengers’ flow across the borders. The border security officials have affirmed that the systems have aided in preventing fraud and strengthening border and national security helped prevent fraud and strengthener” program, where 90% of its 35 million annual travelers entering the program would do so through a paperless biometric recognition system (Yang et al., 2019). Consumer biometrics are now increasingly adopted in terms of surveillance systems and mobile phones using the systems for and authentication. Also, the financial market has presented the most mature biometric market as it seeks to protect its customers’ money. Currently, a new Mastercard has been introduced with an embedded fingerprint reader for authentication purposes during card payment processes (Yang et al., 2019). It is also prudent to note that these sectors have constantly sought to develop biometric systems to fully exploit the physical and behavioral traits used to identify an individual.
A survey by the Pew Research Center in 2019 demonstrated that 56% of surveyed Americans demonstrated trusting law enforcement agencies that use the biometric technologies responsibly, while 59% of them accepted the use of the technologies by law enforcement agencies in the assessment of security threats (Smith, 2019). Also, the American public has higher trust in agencies that use the technologies responsibly than other technology companies and advertisers that use the technologies. The increased acceptance of these technologies from the statistics does show that the people have identified their effectiveness, especially in improving security matters (Smith, 2019). However, these individuals hold their concerns on the technologies concerning their privacy and security, which are determinants of their effectiveness levels.
Despite the increased use of biometrics in different fields, effectiveness concerns are still prevalent. For instance, the facial recognition technologies being used by the FBI have been scrutinized on items of their accuracy levels. While considering how accurate the technologies are, several potential outcomes in the numerous identification searches and the one-to-one verifications are considered. In the facial recognition systems, the possible outcomes include an accurate match which is the true positive result, an accurate non-match or the true negative, an inaccurate match which is the false positive or false alarm, oiran inaccurate non-match who is the false negative (Congressional Research Service, 2020). The false positives could lead to errant investigative leads and false accusations, while the false negatives could lead to losing vital evidence to support a case. The false positives will also pose potential security risks since the border control officers may miss a traveler using an assumed identity (Congressional Research Service, 2020). The consequences of these errors do indicate the importance of not heavily relying on the machines as the determinant factors. The possibilities of these errors happening do point out that these machines are not as effective as required.
Additionally, biometric technologies have demonstrated being fallible in several respects, which the policymakers must acknowledge since this detriment negatively affects the provision of superior security. Apart from the technical issues, the two aspects that challenge the biometric security promise include delivering insecurity when it is deployed by malicious human beings (Jacobsen, 2012). This second source will generate insecurity due to how the agency of the technology materializes when implemented in a particular context. In the latter aspect, biometric technologies are considered a means and have agency potential (Jacobsen, 2012). Therefore, when biometrics perform flawlessly, there are still two challenges that need careful consideration as they are a source of insecurity; human and technological agency. As the biometrics are expanding concurrently, there is the risk that the expanding uses may fail to carefully and thoughtfully consider its limitations, fallibility, and how it could lead to new insecurity forms (Jacobsen, 2012). This does raise concern on how effective they are as stakeholders push to have the technologies deployed.
Notably, it has been noted that the possible outcomes heavily rely on both technical and human factors that determine the overall accuracy of facial recognition searches done by respective officers. The effectiveness of the biometric systems is boosted when the machines work together with human beings. Research is done by the National Academies that tested facial forensic examiners’ ability to match identities across different photographs found that accuracy was at a higher level among the examiners and specialists that were forensically trained facial reviewers and the untrained super-recognizers. This was compared to other control groups incorporated into the research; the research also presented information that compared the state-of-the-art facial recognition algorithms with the best human face identifiers. The research would find that the best machine performed best when in the range of best performing human beings that were professional fasciola examiners. Therefore, while looking into how effective the biometric systems could get, it is evident that human examiners play a fundamental role in how effective they can be.
Furthermore, the biometric technologies’ effectiveness is boosted through a multiple-layer security strategy that will reduce the prevalent vulnerabilities. This strategy is effective since it will provide higher security than the traditional security mechanism but remain vulnerable to threats of spoofing, hacking, theft, tampering, and legitimate template substitution (Gupta, 2008). For instance, fingerprint biometrics can easily be fooled through the use of false prints, fake fingers, or pattern recognition techniques such as the hill-climbing attack. A criminal can obtain a live biometric sample from an authorized user using force. Therefore, biometric technologies’ effectiveness is determined by how these systems can incorporate other security techniques to ensure that even the information remains confidential and not accessible by unauthorized users. The encryption of stored biometric templates and multi-biometrics in conjunction with passwords or digital signatures prevents online threats such as hacking and spoofing. Contactless biometric authentication is being incorporated in particular communities, such as the radio frequency identification (RFID) chips (Gupta, 2008). The fingerprint devices could also bring in the vitality detection mechanisms through measuring optical electric or thermal properties of an individual’s skin or other biometric traits. The iris-recognition devices could measure the involuntary pupillary hippus to make sure that the eye is alive. The resources needed to beat the biometric sensors increase as more vitality mechanisms are introduced (Gupta, 2008). There is still the risk of an unauthorized user thwarting a vitality mechanism if they know of it. The best method for vitality detection should use a distinctive characteristic for each person, and it is not readily available to an enemy for copying. At the moment, the organizations bringing in the biometric systems need to ensure that they have a secure infrastructure to support the process, especially in the distributed network environments.
Biometric technologies have the detriment of being irrevocable; therefore, when one gets compromised, it is compromised forever. In the finance field, users get new cards with limited biometric traits that are the face and fingers that are irreplaceable (Prabhakar et al., 2003). Also, different applications using the risk of similar biometrics do pose the risk of a malicious user acquiring an individual’s biometrics in one application getting to use it in others. Nonetheless, the integration of cryptographic techniques with biometric matches will aid in handling the challenge. For instance, rather than store the original biometric signals within the system database during the initial enrollment stages, the system could store them in the non-invertible transformed version (Prabhakar et al., 2003. The biometric sensor would transform the signals using similar noninvertible transform and conducting matching in the transformed space., different applications also need to use different noninvertible transforms or to have distinct parameters of a similar transform such that one template gets to be used for one application only it is prudent to note that the technique is also invertible. The noninvertible transforms are not strong (Prabhakar et al., 2003). The latter could quickly lower the system accuracy since the matcher cannot effectively handle all the biometric signal variations. Creating an easily revocable biometrics template could incorporate a biometric template encryption using the user’s password. In commercial applications, the decision of adding or replacing existing personal recognition methods in conjunction with biometric-based solutions will need to be based on cost-benefit analysis such that mechanisms brought in bring in better profits.
Given the breadth of knowledge presented by different scholars on biometric technologies, these technologies are crucial within the security realm since they revolutionized different sectors. Nonetheless, it is also evident that these technologies’ effectiveness depends on other factors apart from their technicalities. Issues such as human examiners’ expertise will determine how accurate the technology will be in matching to the right person. Also, biometric systems are more effective when combined with other security mechanisms such as cryptographic mechanisms.
Nonetheless, there are still numerous concerns related to biometric technologies. The present deployment and literature on the technologies have still not found solutions to these challenges. Therefore, there is a need for resources to facilitate constant research on advancing knowledge on biometric technologies. Further research is also required in the societal, political, and ethical implications of the developments and applications (Jacobsen, 2012). It is essential that a better appreciation of the strategies in which the development and deployment of biometrics technology, especially as a security technology, is done considering that they can alter the power balance between persons and authorities. The knowledge in these matters should aid in the responsible deployment of the technologies without compromising individual rights. The system operators and authorities must also create proper judgments on a person’s safety without putting the entire trust on biometric identification (Jacobsen, 2012). As noted, these systems have a risk of potentially identifying or authenticating the wrong person. Therefore, it is about having integrated security systems that could identify the right persons while offering maximum security. Additionally, considering the likelihood of failure, it is also recommended that high priority is given to implementing measures that increase the potential for individual redresses, such as when the identification processes have made a false match. Trusting the technology thoroughly and having no redressal mechanisms would mean that even the simple technological failures can lead to insecurities that confront the very persons protected in the biometric technologies.

References
Accenture. (2012). Biometrics and privacy: A positive match. How organizations can use biometrics technologies and protect individuals’ privacy in the journey to high performance. Retrieved from https://www.accenture.com/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Dualpub_9/Accenture-Biometrics-Privacy-Positive-Match.pdf
Congressional Research Service. (2020). Federal Law Enforcement Use of Facial Recognition Technology. Retrieved from https://fas.org/sgp/crs/misc/R46586.pdf
Gupta, B. (2008). Biometrics: Enhancing Security in Organizations. IBM Center for the Business of Government.
Jacobsen, K. L. (2012). Biometrics as security technology: Expansion amidst fallibility (No. 2012: 07). DIIS Report.
Prabhakar, S., Pankanti, S., & Jain, A. K. (2003). Biometric recognition: Security and privacy concerns. IEEE security & privacy, 1(2), 33-42.
Smith, A. (2019). More Than Half of U.S. Adults Trust Law Enforcement to Use Facial Recognition Responsibly. Pew Research Center.
Yang, W., Wang, S., Hu, J., Zheng, G., & Valli, C. (2019). Security and accuracy of fingerprint-based biometrics: A review. Symmetry, 11(2), 141.

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