Automated Facial Recognition Authentication (AFRA) - Benefits, Problems, and Implications

This article discusses the benefits, problems, and implications of the Automated Facial Recognition Authentication (AFRA) system proposed by the state government for identifying and authenticating users to access state-level services. It analyzes the possible benefits and problems of the AFRA system for license recommencement, implications for an individual's privacy, ethical and privacy implications of state police's proposed use of AFRA, and personal implications of the AFRA proposals. The article concludes that while AFRA has potential benefits, it also carries significant privacy and security concerns that need to be addressed before implementation.

Running head: CLOUD PRIVACY
Automated Facial Recognition Authentication (AFRA)
Name of the Student:
Name of the University:
Author Note:

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Table of Contents
Introduction:........................................................................................................................2
Possible Benefits and Problems of AFRA system for License Recommenceal:.................3
Implications for an Individual's Privacy..............................................................................4
Ethical and privacy implications of State Police’s proposed use of AFRA:.......................6
Personal Implications of the AFRA Proposals:...................................................................8
Conclusion...........................................................................................................................9
References:........................................................................................................................11

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Introduction:
The identification of an identity depending upon the facial trait is a kind of biometric
device that is consisted of special type of software which carries the ability of verification or
identification of a unique person (Amos, Ludwiczuk & Satyanarayanan, 2016). For achieving
similar goal this software is designed to recognize the face pattern of individual person and make
a comparison between the achieved and stored data of this software’s database. If the collected
data got the similarity with that of stored information in the software’s database, then the method
of authentication and verification is considered to be completed. Use of this software is basically
for the reasons of security related issues as well as a solution to numerous security solutions
(AbdAlmageed et al., 2016). Now a day this kind of software got a huge popularity and success
in practical field as well as carries the potential to get used in authentication process of several
organization and institutes of concern.
The procedure of recognition depending upon facial authentication carries a great
potential to get used in the future technological atmospheres as well as have the ability of doing
any kind of transaction just making a trace of authenticated user. This kind of software practices
liveness detection of next generation and the data point of facial for accruing the authentication
of the requested access of the user. In the usage of this type section by the government of the
state took the decision of implementing the authentication of using the facial recognition in the
aim of identifying and authenticating that will have the ability of enhancing and amplifying
various type of services at state level. But the governing authority is still unable to use and
implement of the recognition authentication depending upon facial detection (AFRA) system.

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But the government has not decided the implementation process of the AFRA(automated
facial recognition authentication) system. To support the complexity of successful
implementation in practice by the government the use of it is thoroughly discussed in this paper.
In this case the procedure implementation of the AFRA system as well as the cons related is
discussed. With potential benefits of it in respect with the probable issues that could be faced by
the user of it is analyzed in this report.
Possible Benefits and Problems of AFRA system for License Recommenceal:
To accept any time of governmental requests and authenticating the application of
applicant is the field where the system of AFRA could be implemented effectively. This type of
licensing procedure includes firearm license, driving license or in any type of activities that is
needed to get approved by governmental bodies. For this procedure of authentication, application
for new permission or extend the validation of the license one uses to apply through manual
documents to the authority of concern (Nordbakke, Sagberg & Gregersen, 2016). Automated
verification of documents of the application in AFRA is easier than the formal procedure, though
it also carries some of the issues in real life practices. Those are discussed thoroughly in bellow
passages.
Benefits: If the authority of concern decides to implement the service of AFRA it will provide a
number of benefits to the requester or the applicant like “One User, One License.” Which
actually provides a number of benefits to the user. While in the case of previous practice there is
prove of having several number of license by a same person just on different names. This type of
false happening of governmental license enables the opportunity for the antisocial for conducting
antisocial activities. (Automated depending upon facial recognition can offer benefits to the
society – if it is supported for the development of properly - IFSEC Global | Security and Fire

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News and Resources, 2019). (Time for an about-face? Flaws in facial recognition plan, 2019).
The automated policy of facial authentication got the potential of eliminating a number of
duplicity a different documents by a same fraud person (Carter, 2018). At the time of application
for license by a user the facial structure of the person gets verifies by the database of AFRA
effectively and strictly. In this way the system of AFRA is able to stop the cases of fraud cases
by the properties of its activities. In this way AFRA is able stop the cases of fraud activities
successfully (Al-Kawaz et al., 2018).
Problems: Though the activities of AFRA got the ability and effectiveness of successful
implementation of detecting fraud and issuing license, but it carries number of cons too. One of
those mentionable problem is issue of authenticating. Basically it is done when a person apply
the license, it first gets matched with the AFRA database. But the problem arises when at the
flow of documents submission it gets hacked by some hacker and leads to a critical situation
(Solanki & Pittalia, 2016). By getting the access to the data of the targeted person’s data it
becomes too easy for the hacker to get an application with the usage of those hacked documents.
By following those act the hacker would easily have the access of authentication on the hacked
victim’s name and commit illegal activities and which case the blame comes on the victim’s
name.
Implications for an Individual's Privacy
Previously it is used to analyse the recognition depending upon the automated facial
authentication process operated by the ARFA which means that it has numerous benefits for the
license section as well as also carrying some crucial threats and issues in the scenario for the
application of new license or license recommence (Evaluating the use of automated facial
recognition technology in major policing operations, 2019). The main issue that takes place in

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this scenario relevant to the privacy issues of the person who tries to apply for new availability of
license or recommence related to that of the licenses. In this case the AFRA or facial recognition
through automated authentication maintains the individual’s in several ways. This system is
implemented by the government of state in the purposes of licensing and it leads to the creation
of some issues related to privacy as the coding and algorithm used for designing this system’s
type is not transparent publicly. Thus several question arises regarding working and accuracy
functions related to system. For this factor the automated recognition of facial authentication
system is consisting of major implications in the case of individual’s privacy rights. This threats
could become worse at the time of discrimination and biasness that occurs in the practices of
policing (Leong, 2019). In this report the automated identification of the facial authentication
system could also interrupts those rights of peoples by utilizing few unique algorithm with
personal characteristics (Facial Recognition and its Security Flaws, 2019). For the reason all the
stand alone individual’s characteristics turns into few digital data that enables surveillance as
well as analysis of these peoples. The information are deposited in the system’s server that is
operated and supervised by the government of state and those data are stored for a long time
(Why regulating facial recognition technology is so problematic - and necessary, 2019). For such
cause, it always carries some potentiality for the hacking and defrauding.
This automated authentication of facial recognition or the system AFRA could explain the
mankind to the discrimination of potential in two ways. For the first scenario number of agencies
of government can misuse this technology of AFRA in connection with few demographic groups
intentionally or unintentionally. For the second scenario it is determined that persons with
minorities or ethnics and the skin color dark or nearer to dark women are sometimes
misidentified for this system in higher rates at the time of comparison with other populations

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(Gui, Baltrušaitis & Morency, 2017). For the problem related to accuracy there could be number
of problems which could lead to person of some unique collections being marked by several
types of security or number of policies measures that could be inapplicable for them. For this
kind of various key privacy related application could occur for the AFRA utilization in the
section of licensing.
Ethical and privacy implications of State Police’s proposed use of AFRA:
There are various problems of individuals with respect to the ethical implications of the
State police’s proposed use of the AFRA. The different ethical issues are described below:
Error: While the public monitoring and surveillance many errors may happen. The errors can be
done by many factors. One of primary factor is the implementation of the camera in the system.
The camera may unable to match the right person and that person due to the lack of recognition
cannot the access the system and error can occur. The wrong match can also arise many
problems in the system. The Wrong access in the system can lead to various types of losses such
as loss of information, efficiency loss of the system, hacking and so on. The wrong identification
of the culprits can harass the public and lead to many damage to the common people of the state.
The police will able to determine the fault in the system and will easily trust the system and will
arrest honest people instead of arresting the culprits (Phillips et al., 2018). The error is not
limited to the camera of the system. Another common error that can occur is the misuse of the
database which is used to store the data of the facial recognized person. The database should be
kept secured and the misuse of the database should be not tolerated. The wrong recognition
should be avoided by the system as the new report, 2019 stated that 98% cases fail in Automated
Facial Recognition Technology.

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Function Creep: Another kind of ethical issues in the implication of the AFRA system is the
function creep issue. The function creep can be defined as the process where a particular
technology is developed for a limited functionality and achieves additional functionality
((Vervaele, 2017). This type of error can occur where there is a huge usage of the system as well
as because of some systematic problems. Such type of efficiency should be included by police to
search the missing peoples by the recognition process of criminals. The flexibility of system can
rise rate of the function creep and can cause damage to the police and common people. The most
common way to attack the system by function creep is by broadening the database of the system
(Facial recognition: is the technology taking away your identity, 2019). Databases used in the
system of AFRA can be widened easily or they can be merged with supplementary databases that
are utilized by the State Government. Thus, in this particular way various new and unrecognized
peoples may be included in the database and they will be monitored as well. Thus many
problems can occur due to this expansion of the databases (Pawle & Pawar, 2013).
With addition to the ethical implications, the privacy related implications can also
hamper the daily life of people and police. The various privacy related issues or problems are
described below:
Data collection without informing people
There are various recognition system available in the market which generally recognize
people by some of their traits. For example bio metric system. In this case the individual should
touch or feel the system before gaining the access to the system (Datta, Datta & Banerjee, 2015).
Thus, the individual is aware of the process but in case of AFRA an individual is unaware of the
access method. In case of the biometric system the individual is aware of the fact that he or she is
entering his or her information in the system where the data is not taken forcefully from the user

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but in AFRA system it has an ability to collect the data of the individual without the
acknowledgement of the people. This may lead to huge privacy concern (Evison & Bruegge,
2016). Moreover the user cannot resist the AFRA system from storing the disallowed
information by the system (Ren, Jiang & Yuan, 2013). Thus new policies should be introduced
which justifies that the data should be collected only for those peoples who wish to make a new
license or request to recommence their driving license but in this case, the proposed AFRA
system will collect the data without the acknowledging people which will create huge privacy
related problems as the system will store the data without the proper knowledge of peoples.
Personal Implications of the AFRA Proposals:
In this particular case the AFRA system is designed for providing new license to the
consumer and also is used to recommence the existing license of the consumers. If the system
stores information for providing new license then the system will be appropriate and acceptable.
Some issues in the current technology of the AFRA. It can end the possibility of duplicity of
licenses. The system can be developed more to satisfy the privacy and security factors but it is
recorded that AFRA contains many issues regarding the licensing purpose (Kataria et al., 2013).
The possibility of hacking can be lowered by developing the security of the system which
eventually attract peoples towards it. Thus, the system can be used after the development is done
successfully.
The AFRA system is not suggested for the proposal of state police where it can be
utilized for public surveillance as the privacy and security concern for both the cases are
different and are variable. The public surveillance is done with the proper acknowledgement of
people and thus generate many privacy issues. The system is proposed for licensing and
recommencing the existing license for the consumers. The Security and privacy related issues

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should be overcome by the system then only the system can be implemented and used properly.
The main aspect is that the system should operate efficiently without hampering common people.
The ethical issues should also be considered and should also be avoided by the system. Thus, the
security and privacy concerns will not be maintained if police proposal is granted.
Conclusion
Therefore, from the above report it can be concluded that Facial recognition play an
important role in the authentication process of a system. It is considered to be a major way to
determine an individual by verifying some of the individual traits. The report also discussed that
there are some huge problems regarding the implementation of the AFRA system which is
proposed by state government to authenticate and identify user. This is proposed to access
different types of the state level services. Initial trial of automated facial recognition
authentication system is done by implementing it to provide and recommence license for the
boats, vehicles and firearms. The report also discussed the benefits of the automated facial
recognition authentication system. The total mechanism of the operation is mentioned or
discussed in this report. Two main operations are carried out by the automated facial recognition
authentication system, first provide new license to the consumer and to recommence the existing
license of the drivers. The report also discussed various ethical and privacy issues of the
automated facial recognition authentication system while granting the proposal made by the state
government. The implication for the individual’s privacy is also discussed in this report. The
privacy issues regarding the proposal of the state policy are also discussed in this report. The
main issue is the security factor of the system. The various issues should be resolved such that
the system can be implemented and can be used to provide license or to recommence the existing
license of the consumers. The individuals have to face many problems by the implementations of

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automated facial recognition authentication system. Lastly, this report discussed both the
proposals. The report also concluded that the proposal of the licensing is acceptable when the
security of the system is developed. The security is the main concern of the proposed automated
facial recognition authentication system. Thus, the security and privacy of the automated facial
recognition authentication system will impact negatively on the individuals.

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References:
AbdAlmageed, W., Wu, Y., Rawls, S., Harel, S., Hassner, T., Masi, I., ... & Nevatia, R. (2016,
March). Face recognition using deep multi-pose representations. In 2016 IEEE Winter
Conference on Applications of Computer Vision (WACV) (pp. 1-9). IEEE.
Al-Kawaz, H., Clark, N., Furnell, S. M., Li, F., & Alburan, A. (2018, June). Advanced facial
recognition for digital forensics. In 17th European Conference on Cyber Warfare and
Security(pp. 11-19). Academic Conferences and Publishing International Limited.
Amos, B., Ludwiczuk, B., & Satyanarayanan, M. (2016). Openface: A general-purpose face
recognition library with mobile applications. CMU School of Computer Science, 6.
Automated facial recognition can benefit society – if we support its development properly -
IFSEC Global | Security and Fire News and Resources. (2019). From
https://www.ifsecglobal.com/access-control/automated-facial-recognition-benefit-
society-support-development-properly/
Automated facial recognition technology wrong in 98% of cases, says new report. (2019). From
https://www.governmenteuropa.eu/automated-facial-recognition-technology-report/
87498/
Carter, A. (2018). Facing Reality: Benefits and Challenges of Facial Recognition Technology for
the NYPD. Homeland Security Affairs.
Datta, A. K., Datta, M., & Banerjee, P. K. (2015). Face detection and recognition: theory and
practice. Chapman and Hall/CRC.

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Evaluating the use of automated facial recognition technology in major policing operations.
(2019). From https://phys.org/news/2018-11-automated-facial-recognition-technology-
major.html
Evison, M. P., & Bruegge, R. W. V. (Eds.). (2016). Computer-aided forensic facial comparison.
CRC Press.
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https://www.internetandtechnologylaw.com/bias-facial-recognition-flaws/
Facial recognition: is the technology taking away your identity? (2019). From
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identity-tesco-ethical-issues
Gui, L., Baltrušaitis, T., & Morency, L. P. (2017, May). Curriculum learning for facial
expression recognition. In 2017 12th IEEE International Conference on Automatic Face
& Gesture Recognition (FG 2017) (pp. 505-511). IEEE.
Kataria, A. N., Adhyaru, D. M., Sharma, A. K., & Zaveri, T. H. (2013, November). A survey of
automated biometric authentication techniques. In 2013 Nirma University International
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Leong, B. (2019). Facial recognition and the future of privacy: I always feel like… somebody’s
watching me. Bulletin of the Atomic Scientists, 75(3), 109-115.
Nordbakke, S., Sagberg, F., & Gregersen, F. (2016). The end of passion? Changes in driving
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Pawle, A. A., & Pawar, V. P. (2013). Face recognition system (FRS) on cloud computing for
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Phillips, P. J., Yates, A. N., Hu, Y., Hahn, C. A., Noyes, E., Jackson, K., ... & Chen, J. C. (2018).
Face recognition accuracy of forensic examiners, superrecognizers, and face recognition
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