Introduction

Biometrics is the science of identifying and classifying individuals based on their measurable traits and behaviours. Identifying people who are subjected to surveillance or controlling who has access to restricted areas are two of the most common applications of this technology. For biometric authentication to work, it must be based on the principle that every individual may be uniquely recognised by some combination of observable physical and behavioural characteristics. The two Greek elements “bio” (representing life) and “metric” (meaning measurement) form the root of the word biometrics. Typing habits, mouse as well as finger motions, interaction patterns with blogs and social media, strolling stride, as well as other gestures may all be used as behavioural identifiers. In place of a one-and-done authentication check, several behavioural identifiers may be utilised to enable continuous authentication. Despite its infancy and poor reliability scores, this method has the capability to develop in tandem with advances in biometric systems. In this blog, the main topic which will be discussed is the risks and the dangers of biometrics. In the following sections, there will be a discussion about the methods, types and risks related to biometrics. In the end, get the help for Online assignment help there will be recommendations and a conclusion on the basis of the blog.

Features of Biometrics

Regulating Entry

Biometric systems can be used  to write that essay for more than just keeping a record of time; they could also be utilised for security purposes, such as preventing unauthorised individuals from entering restricted parts of the facility (Gui et al. 2019). It should look for gadgets that provide built-in access control features. Organizational security and efficiency may both benefit from integrated systems.

The potential of the User

Even if It yourr company only has a few workers now, It should still search for a “biometric attendance system” that can save and verify a large number of patterns (face, fingerprints, palm, etc.). As the company expands so over years, the gadget may be used to sign up new workers.

Connectivity

The biometric devices need to be connected to the internet, research proposal help. The time that workers clock in and depart is sent via scanners to the HRM attendance as well as payroll system. Having access to the internet is required for system updates and bug-free operation for the foreseeable future. Since we’re already discussing network options, let’s also include USB support, which may be used to rapidly and easily back it up data to an “external device” in case of emergency.

The Identifying Phase

The speed with which a biometric device can make an identification is crucial to the efficiency of an attendance monitoring system that relies on biometric data. It’s important to have a reliable way to keep track of employees’ attendance (Özdenizci et al. 2019). It’s worth it to shop around for devices that can do so in a matter of seconds and then automatically upload that information to a database. ” Matrix COSEC Face Recognition”, for instance, needs just around two seconds to make a positive identification.

Ruggedness and durability

Consider purchasing equipment that is dusty and grime resistant, can withstand severe temperatures, but also is built to last. In addition to being waterproof and resistant to scratches, the optical sensors in “fingerprints time-attendance systems” like “Matrix COSEC ARGO” are also scratch-proof (Akhtar et al. 2018). This guarantees that the “time-attendance system” will always function flawlessly, no matter the conditions or how it is handled. Moreover, It should ensure that the solution is not vulnerable to dust as well as water.

Connectivity to Human Resources Information Systems

The system’s information is crucial to the development of more efficient HR payroll administration solutions. With accurate records of the attendance system, the HR department can swiftly and accurately calculate pay for all workers (Kumar et al. 2018). Select tools that can transmit information to the human resources payroll system automatically.

Support

Even while “biometric attendance systems” are simple to set up and use, It may sometimes need help from a professional. Always go with a trusted brand like Matrix that backs up the gadget with excellent customer care, both available on the internet and in-store.

Examples

There are many types of biometrics there for recognition. The methods are-

• Fingerprint scanning
• Voice recognition
• DNA
• Heart-rate sensor
• Facial recognition

Risks

Invulnerable to security breaches

Using biometrics to verify It r identity is a safe and reliable method. However, biometric information may still be stolen (Pope, 2018). The biometrics may be obtained by any bad actor who gains the database’s access (Meden et al. 2021). Attackers may obtain personal biometrics and use them for malicious reasons, posing a threat not just to the company It works for but to It r own personal safety as well.

Privacy

A person’s biometrics are a unique physical trait. This means that it may be a privacy issue if someone else were to get information to personal biometrics without its knowledge (Gupta et al. 2019). The most vulnerable kind of biometric identification is facing recognition since an intruder who gains the database’s access may then use that information to steal the identity.

Figure 1: Attacks in the system of Biometrics

(Source: researchgate.net, 2018)

Dishonesty and a lack of accuracy

Few biometric systems make advantage of full biometric information. Data is stored in its entirety, but only a subset is used during authentication to save time and account for any inconsistencies (Madianou, 2019). As a result, these systems only make use of a subset of the biometrics information collected. This means that authentication isn’t always reliable and that fraudsters may circumvent security measures by learning which pieces of information are being used in the verification process.

Complexity and Failures in the System

It’s not a perfect world in which people live. So, naturally, mishaps may and do occur. For biometric identification systems, errors may be quite inconvenient. In scenarios where this is an available authentication method, it may not be a huge concern (Brown, 2020). If the phone’s fingerprint reader, for instance, stops operating, it may still unlock it using a passcode or the owner’s face. The issue, however, arises when biometric authentication is required yet the system fails (Sudharsan et al. 2022). If fingerprint authentication is required to enter a room, for instance, as well as the scanner being broken, customers won’t be able to enter until either the scanner is repaired or the security system is bypassed.

Medical field-related risk

Cybercriminals have many chances to steal confidential material, such as client medical data, clinical study findings, and proprietary information linked to medication development, thanks to IT weaknesses in the “Healthcare Technology and Life Science business” (Mohsin et al. 2018). Since it may be used for health coverage deception, and identity fraud, including, in the instance of drug research, selling upon that black market to imitation medicine traffickers, a $75 billion yearly business, this data is much more important to attackers than credit card information taken through internet phishing tactics (Alsaadi, 2021). As the possibility for ‘bio-crime’ increases in the coming years, the safe storage of this data will become an integral part of “security planning” within this business. Because of this widespread use of biometric security measures, there is an obvious danger of identity theft and economic fraud to people whose fingerprinting or DNA profiles are taken and replicated for impersonation or healthcare fraud (Godfrey et al. 2021). Companies in the healthcare and life sciences industries, in particular, have to take the appropriate steps to make sure that their employees fully grasp the security protocols required to avoid a data leak, as cybercriminals place a high value on personally identifiable medical information such companies’ store.

Improvement of biometrics security

• Biometric data should not be disclosed or compromised unless there is tight coordination between the administration, the corporate sector, plus civil society. Countries confront additional cybersecurity issues while creating “digital identity ecosystems”, such as maintaining the security, privacy, and accessibility of sensitive information (Masala et al. 2018). There, several stakeholders may provide viewpoints that must be weighed in order to forestall any damages that might result from the system’s abuse, exploitation, or hacking.
• The leadership issue of controlling cyber risk has been significant in both the public and commercial sectors. As a result, it may be difficult to gauge the appropriate kind and degree of investment in cybersecurity, as well as hard to see the risks associated to cyber threats (Khoo et al. 2018). Leadership throughout the world should think about the potential for damage posed by the abuse or exploitation of technology, and take steps to ensure that these tools are put to positive use by including many perspectives in their development.
• Personal information is protected by replicas that prevent it from being used or disclosed in an unauthorized manner. As a result, biometric data must only be shared or utilized for its original purpose (unless an extraordinary one applies). Fingerprint biometrics, for instance, obtained for the goal of controlling entry into and exit from a place should never be utilized for any other reasons, such as tracking the whereabouts of the persons for whom they were collected. Functionality creep may be avoided by clearly outlining how biometric data is supposed to be used or shared.

Figure 2: NGBS

(Source: ngbs.athene-center.de, 2022)

Recommendations

• Prior to deciding whether or not to adopt or install biometric technology, VPS organizations should conduct a “Privacy Impact Assessment (PIA)”. If a business wants to know the full extent to which an effort will affect users’ privacy, what dangers could be involved, and how to prepare for them, it should conduct a PIA.
• Since a person’s unique biometric traits are not readily altered like passwords or ID tokens, it is crucial that this data be kept secure at all times. Organizations operating in the “Victorian Public Sector (VPS)” have a duty to take precautionary measures to preserve the confidentiality, integrity, and availability of any “Personally Identifiable Information (PHI)” they collect, use, or disclose. This includes biometric data.
• The monitoring and responsibility of technologies are crucial to ensure they are utilized responsibly, making governance another vital issue to think of when adopting and deploying biometrics (Rajasekar et al. 2022). In the event that biometric information was misused or there are flaws in the biometrics, organizations using such technologies ought to have open channels for complaints and inquiries in place, as well as identify the proper external and internal routes for redress. It is equally crucial that end users be made aware of these complaint procedures and available options for resolution.
• When choosing a biometric, accuracy is important, but it shouldn’t be the only element to think about. Other considerations include how easy it is to use, how fast it is, how widely available it is, and how well-accepted it is. Additionally, it is crucial that the right biometric sample be assigned to the enrolled at the time of enrolment. To reduce the possibility of mistakes during the enrolment and continuing usage and maintenance of a biometric system, individuals will need proper training and assistance.

Conclusion

It can be concluded that when it comes to identifying and categorizing people, biometrics is the way to go. One of the most popular uses for this technique is in determining who is allowed into restricted areas or identifying those who are under observation. To function properly, the biometric devices must be online. Employees’ arrival and departure times are sent through scanners to the human resources management and payroll system. To avoid bugs and ensure continued smooth functioning, a connection to the internet will be necessary in the near future. Identity verification with biometrics is a secure and trustworthy process. Biometric data may still be taken, however. Anyone with access to the database could steal the biometric information. Since an attacker who obtains the database’s access might use that knowledge to steal someone’s identity, facial recognition is the weakest method of biometric authentication. Numerous opportunities exist for cybercriminals to steal sensitive information, such as patient’s medical records, the results of clinical trials, and trade secrets related to the creation of new medications. For this company, “security planning” will include the secure storage of this data as the likelihood of “bio-crime” grows in the future years. World leaders should consider the risks associated with the misuse or abuse of technology and take measures to guarantee that these resources are put to good use by including a wide range of viewpoints. Another important consideration when adopting and implementing biometrics is administration, which involves the monitoring and management of technologies to guarantee their responsible use.

Reference

Akhtar, Z., Hadid, A., Nixon, M.S., Tistarelli, M., Dugelay, J.L. and Marcel, S., 2018. Biometrics: In search of identity and security (Q & A). IEEE MultiMedia, 25(3), pp.22-35. https://infoscience.epfl.ch/record/231119/files/Akhtar_IEEEMM_2017.pdf

Alsaadi, I.M., 2021. Study on most popular behavioral biometrics, advantages, disadvantages and recent applications: A review. Int. J. Sci. Technol. Res, 10, pp.15-21. https://www.researchgate.net/profile/Israa-Alsaadi-2/publication/348662448_Study_On_Most_Popular_Behavioral_Biometrics_Advantages_Disadvantages_And_Recent_Applications_A_Review/links/6009c63b299bf14088b188e8/Study-On-Most-Popular-Behavioral-Biometrics-Advantages-Disadvantages-And-Recent-Applications-A-Review.pdf

Brown, E.A., 2020. A healthy mistrust: curbing biometric data misuse in the workplace. Stan. Tech. L. Rev., 23, p.252. https://law.stanford.edu/wp-content/uploads/2020/06/Brown-A-Healthy-Mistrust.pdf

Godfrey, A., Vandendriessche, B., Bakker, J.P., Fitzer‐Attas, C., Gujar, N., Hobbs, M., Liu, Q., Northcott, C.A., Parks, V., Wood, W.A. and Zipunnikov, V., 2021. Fit‐for‐purpose biometric monitoring technologies: leveraging the laboratory biomarker experience. Clinical and translational science, 14(1), pp.62-74. https://ascpt.onlinelibrary.wiley.com/doi/pdf/10.1111/cts.12865

Gui, Q., Ruiz-Blondet, M.V., Laszlo, S. and Jin, Z., 2019. A survey on brain biometrics. ACM Computing Surveys (CSUR), 51(6), pp.1-38. https://dl.acm.org/doi/pdf/10.1145/3230632

Gupta, S., Buriro, A. and Crispo, B., 2019. DriverAuth: A risk-based multi-modal biometric-based driver authentication scheme for ride-sharing platforms. Computers & Security, 83, pp.122-139. https://bia.unibz.it/esploro/fulltext/journalArticle/DriverAuth-A-risk-based-multi-modal-biometric-based-driver/991006214998601241?repId=12266718880001241&mId=13266778900001241&institution=39UBZ_INST

Khoo, Y.H., Goi, B.M., Chai, T.Y., Lai, Y.L. and Jin, Z., 2018, June. Multimodal biometrics system using feature-level fusion of iris and fingerprint. In Proceedings of the 2nd International Conference on Advances in Image Processing (pp. 6-10). https://www.researchgate.net/profile/Tong-Yuen-Chai/publication/345572843_Multimodal_Biometrics_System_Using_Feature-Level_Fusion_of_Iris_and_Fingerprint/links/634e0b6796e83c26eb32be37/Multimodal-Biometrics-System-Using-Feature-Level-Fusion-of-Iris-and-Fingerprint.pdf

Kumar, S., Singh, S.K., Singh, A.K., Tiwari, S. and Singh, R.S., 2018. Privacy preserving security using biometrics in cloud computing. Multimedia Tools and Applications, 77, pp.11017-11039. https://www.academia.edu/download/86305877/s11042-017-4966-520220522-1-lzti8e.pdf

Madianou, M., 2019. The biometric assemblage: Surveillance, experimentation, profit, and the measuring of refugee bodies. Television & New Media, 20(6), pp.581-599. https://research.gold.ac.uk/id/eprint/26447/1/The%20biometric%20assemblage%20FINAL.pdf

Masala, G.L., Ruiu, P. and Grosso, E., 2018. Biometric authentication and data security in cloud computing. Computer and network security essentials, pp.337-353. https://e-space.mmu.ac.uk/623238/1/proposal_final_revision2_stamp.pdf

Meden, B., Rot, P., Terhörst, P., Damer, N., Kuijper, A., Scheirer, W.J., Ross, A., Peer, P. and Štruc, V., 2021. Privacy–enhancing face biometrics: A comprehensive survey. IEEE Transactions on Information Forensics and Security, 16, pp.4147-4183. https://ieeexplore.ieee.org/iel7/10206/9151439/09481149.pdf

Mohsin, A.H., Zaidan, A.A., Zaidan, B.B., Ariffin, S.A.B., Albahri, O.S., Albahri, A.S., Alsalem, M.A., Mohammed, K.I. and Hashim, M., 2018. Real-time medical systems based on human biometric steganography: A systematic review. Journal of medical systems, 42, pp.1-20. https://www.researchgate.net/profile/Israa-Alsaadi-2/publication/348662448_Study_On_Most_Popular_Behavioral_Biometrics_Advantages_Disadvantages_And_Recent_Applications_A_Review/links/6009c63b299bf14088b188e8/Study-On-Most-Popular-Behavioral-Biometrics-Advantages-Disadvantages-And-Recent-Applications-A-Review.pdf

Özdenizci, O., Wang, Y., Koike-Akino, T. and Erdoğmuş, D., 2019. Adversarial deep learning in EEG biometrics. IEEE signal processing letters, 26(5), pp.710-714. https://ieeexplore.ieee.org/ielaam/97/8671680/8675355-aam.pdf

Pope, C., 2018. Biometric data collection in an unprotected world: Exploring the need for federal legislation protecting biometric data. JL & Pol’y, 26, p.769. https://brooklynworks.brooklaw.edu/cgi/viewcontent.cgi?article=1570&context=jlp

Rajasekar, V., Predić, B., Saracevic, M., Elhoseny, M., Karabasevic, D., Stanujkic, D. and Jayapaul, P., 2022. Enhanced multimodal biometric recognition approach for smart cities based on an optimized fuzzy genetic algorithm. Scientific Reports, 12(1), pp.1-11. Rajasekar, V., Predić, B., Saracevic, M., Elhoseny, M., Karabasevic, D., Stanujkic, D. and Jayapaul, P., 2022. Enhanced multimodal biometric recognition approach for smart cities based on an optimized fuzzy genetic algorithm. Scientific Reports, 12(1), pp.1-11.

Sudharsan, B., Corcoran, P. and Ali, M.I., 2022. Smart speaker design and implementation with biometric authentication and advanced voice interaction capability. arXiv preprint arXiv:2207.10811. https://arxiv.org/pdf/2207.10811