Initial Privacy and Security Assessment in AFRA Assignment Sample

Why current AFRA systems as they make the user's information and person details vulnerable to cyber-attacks.

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Initial Privacy and Security Assessment  Assignment Sample

1. Introduction

In the world of rising crime and security issues both in real and virtual world, innovators are coming up with some one-of-a-kind innovations to safeguard people from such illicit activities. One of such innovation is the Automatic Facial Recognition application. It is a technology which is able to identify a person from video, image, or in real. It compares a particular facial features from a given image or data. It is a part of a Biometric Artificial Intelligence. However, even after so much advancement and technological development, no technology can beat the human ability to recognise face. This paper explores the benefits and issues associated with the AFRA, its implications and security issues for the government and individual users. In addition to this, the paper also present an argument on using AFRA by the police and government for licensing purpose and effects on stakeholders’ security.

2. Benefits and Issues with AFRA

It is given in the case that the State government is planning to make use of Automate Facial Recognition Authentication System (AFRA). However, before planning to implement such decisions, it is important to know both pros and cons of this model (Hanson, 2018).

The benefits are explained below:-

  1. Easy and convenient for use:The person just by his/her face credentials can get or renew his/her license anytime and from any place. These system offers least invasiveness and without even much of a training, one can make use of it(Wickes, 2018).
  2. Time Saving:AFRA would be very fast and quick which is the major advantage for the licensees. Unlike other traditional methods, identification of an individual is done in a matter of seconds. For those with tight schedule, this invention can turn out to be very beneficial(De Marsico,, 2014).
  3. User-friendly:The system is not only easy to install but it is user-friendly also. The government can install the system at multiple stations can be able to provide license to multiple applicants at the same time. No special training is required to provide to the applicant as well as the officials.
  4. Versatility:The system can be used by corporations at security checkpoints and license verification. Also, they can be installed at the toll gates for security. Moreover, they can be installed for financial transactions, noting employee’s attendance and time(Hanson, 2018).
  5. Scalability:AFRA system is flexible and one can also say that it is quite scalable. The users and government can use it on higher version of sensors and security systems as per their needs. For a lowest level, its design can be alter to make it less discriminative, whereas for the high level, one can make it with some discriminable features in order to increase the accuracy in identification.
  6. Improve the Crime Controlling System:As per the case, the State Police is all set to install the biometrics on major streets and toll plaza of the town. This would help them in identification of any suspicious individual or criminal leaving or entering the town. They can track his/her location and caught them right away. It compares and analyse the patterns as per the facial contours and features. This can be very effective in controlling (Horikawa, 2019).

Downsides of AFRA

There are numerous factors that can be said downsides of the AFRA. These have been discussed below:-

  • Lack of understanding of different real-world scenarios: The real challenge in face detection is to work in different scenarios where subject’s acquisition phase is unconstrained. Many a time, even a low-resolution or poor illusion picture can be provided access to the information. Due to many similar cases of fraudulent in the past, the use of the AFRA is under investigation(De Marsico,, 2014).
  • Impingement on Right to Privacy: The algorithm of the AFRA is questionable and some researchers claim it to be lesser transparent. The user information can be altered or stolen without the consent of the person applied for the license(Hanson, 2018).As personal signature of the applicants are also stored along with the AFRA data, there is high risk of signature forgery and people can be harmed in financial terms(Horikawa, 2019).
  • Robustness problems with the current AFRA: As most of the functional tests associated with the security feature of the AFRA are conducted in well controlled environment, these system can be altered by any unidentified scenario. Even a small similarity in the face can provide access to the information to any random person. Hence, robustness issue is always a great concerned for the licence applicants(Wickes, 2018).
  • Adversity in recognising physical changes: The model of AFRA is also prone to adverse impacts of the changes in the physique of a person. It has been noticed that if a raw picture of an individual is captured in the beginning and in the later year, the person become fat or facial hair grows in the meantime, then the face recognition system might not recognise him at the time of license renewal. This may cause inconvenience to the applicant(Horikawa, 2019).

3. AFRA and Implications for an Individual's Privacy

As the government has said that the AFRA services will only be used initially for the licensing purposes for vehicle, firearms and boats, it is required to assess the implications from the user’s privacy perspective. In this section, the privacy related issues are discussed in detail. Although, privacy is an issue associated with each and every modern firm and government database. Each and every information gathered by the AFRA of the licensee is stored online. Any person with access to such storage device can alter the information and cause harm to the individuals. AFRA(Hanson, 2018). Moreover, if any person’s face is similar to any criminal, then this system may deny the firearms license to him/her. This is another major concern with the facial recognition system. In fact, this can be stated that the system is discriminative. Many researches have also proved that the system is not 100% accurate as it causes discrepancies in case of women and ethnic minorities. At present, the system can be put under the obligations of racial discrimination laws(Wickes, 2018).

Moreover, this system is very vulnerable to hacking and the information can be used without the consent of the any applicant(De Marsico,, 2014).If any hacker manages to get the picture of the applicant from anywhere, then he/she may be able to get the access of the account. Once the biometric identity is stolen, then it can be used for falsifying legal document, criminal records, or passports. This can do some great amount of damage to person’s social image or financial conditions. Hackers might get access to the bank account, credit card details, or other document and the worst part is that one cannot change the password as the access is provided by facial features and iris that are not replaceable(Horikawa, 2019).

It may also increase the crime as criminals can detain any person and get access to the private information. However, the functional design of the AFRA is not disclosed in the case, but if it only works based on the facial features without considering the iris scan, then this can be a great concern for the individuals’ security. Face ID scan devices used in the AFRA are questionable(Azar&Brostoff, 2014). The government should keep it a dual biometric scan in order to protect the people’s security.

Another implication identified is that AFRA may be unable to identify the twins and provide access to anyone of the information of the other. These implications are very much serious as security bypassing cases by the twins are higher in the world than the forced access to the information or hacking ones. The design of the AFRA may be faulty and a few scientists guarantee it to be lesser straightforward. The client data can be modified or stolen without the assent of the individual connected for the permit. As close to home mark of the candidates are additionally put away alongside the AFRA information, there is high danger of mark falsification and individuals can be hurt in budgetary terms (Wickes, 2018).

Another privacy concern was raised by many researchers and tech-savvy people is the loss of anonymity. While moving on the road or street or in mall, people are going to be recorded by the CCTV cameras. Majority of the cameras are controlled by the private security agencies. By employing AFRA people loses anonymity. The controllers will have the access to the information of individual and about his/her routine(Horikawa, 2019). They may also know how many time a person has passed through a particular route and with whom. AFRA will provide the information to the controller. There is a possibility that the information may be used against the person under surveillance. In addition to this, there has been a huge change in the recent times in the ability of analysing the data and correlating it for drawing insights out of it. This has raised a great concern for people’s privacy(Hanson, 2018).

4. Ethical and Privacy Implications for State’s Police Proposed Use

No doubt that the use of the AFRA in modern policing operations can be a game changer for the State Police Department, the decision should be made after a proper analysis of the proposal. The police department can be able to identify any suspicious individual and can stop him/her right away from doing any harm to the community(De Marsico,, 2014). Many researchers have supported the argument by generating positive results consistently from different tests. These tests are based on many scenarios from real world. Some researchers make use of a number of methods to produce a clear picture and assess the use of AFRA in policing operations systematically. This is important as most of the tests are done considering the ideal and controlled conditions.

The technology used in AFRA comprises two modes: one is live locating an individual as a real-time application that has the ability to scan the faces within the CCTV footage of an area. It looks for a possible match against a particular data or information feed in the system. However, there are some issues. It has been noticed that the relationship between the output produced by AFRA and responses of human operator is ambiguous. The AFRA system usually does not finalise how the output will be used or interpreted; this decision lies in the hand of the operators(Horikawa, 2019). The concern here is that a bias or error in system’s algorithm may result in biased decision-making on the part of operator. For instance, if the system generates numerous identical matches, then operators may defer to the decisions of algorithm and take actions without first verifying the accuracy of the match. On the other hand, if the system generates many false matches, then the operator may override or ignore the match output and miss the correct match(Azar&Brostoff, 2014).

Another issue is of privacy that may arise due to the installation of the cameras on streets and in the public place. The algorithm usually does not consider the problems of personal privacy. The use of the cameras in the public places raise the concern for the violation of right to privacy. Many researchers have argued that even if the expectation of the privacy in the public place is almost nil, people still have the right to the privacy even when they are in the public place. The data is collected, gathered, stored, and analysed on regular basis on a large scale, this is a great violation of personal privacy. In addition to this, this information is stored without the consent of people even when they are roaming or hanging out in the public place (De Marsico,, 2014). Other issues or concern associated with the system is related with electronic harvesting of data that comprise two practices, namely aggregation and shifting information. In the former practice, the data is stored from different sources and a new information is yielded out of it. On the other hand, in the shifting of information practice, the data is changed from one context to another. The personal information collected by AFRA may be sold or altered for political or commercial purpose by the organisation. Hence, data harvesting practices cannot be trusted fully to keep and manage the contextual integrity which is one of the critical conditions of individual’s privacy. Another issue is that AFRA is a biometric technology that digitally encodes people physical aspects, such as facial or iris. There can occur two things: first, this body part is provided a new functional identity which will be used as a password for the data security. This reduces the body part into a key to the information. This can be considered as dehumanisation. However, the police department will enjoy much of a convenienceas much of their work has become automated. However, the major concern related to privacy and security is that in the current world, there is shortage of law enforcement agencies governing AFRA. This can result in creep problems.

5. Personal Implication of AFRA Related Decisions of Government

Talking about the implementation of AFRA in licence application, the system would have both positive and negative impact on the security and privacy. Some of the pros and cons have already been discussed in the previous parts. There will always be two school of thoughts on the use of AFRA in licensing process(Ketchell, 2018).Government’s decision regarding the use of facial biometrics is justified by the argument that it would speed up the process of licensing and would provide convenience to the general public as they can apply for the license from their home(Azar&Brostoff, 2014). No doubt this is a good decision from people’s perspective but one should not completely forget about the security issues associated with it.

The privacy and security related issue will always be there as the information can be stolen by the hackers and can be used against government or any individual(Ketchell, 2018). If these issues are addressed during the designing process and proper consideration is given to the security criteria, then this application can be used for the purpose of licencing purpose (Government Europa, 2018). If the following recommendations are taken into consideration, then the AFRA can be said safe to be used for any public purpose:-

If the AFRA is used wherein the physical premises is controlled by an entity, then such entity should be facilitated to provide prior information or notice to the applicants that the AFRA is used for storing there information in order to get their consent on it. Also, the authorities should be empowered to formulate stringent policies against the misuse of information. The covered authorities are also guided to update their policies regarding the data management. In addition to this, there has to be two gateways for accessing the data. One is AFRA and other is any other biometric or electronic signature(Ketchell, 2018).

Talking about the use of AFRA for policing and surveillance, it can be a great initiative if implemented properly while considering proper laws and regulations set by the government. No doubt that installing cameras can protect men, women, kids, and old people from getting mugged and robbed during night time, but it creates a problem of loss of privacy even in the public places. Constantly, people would be under surveillance without being informed. In addition to this, if any of the information unfortunately gets leaked in the public, then this might result in a blunder from the authority. People would lose trust on the police and chaos may occur. All of the information is stored in the electronic devices and if any technical glitch takes place, then there is no way one can retrieve such a large amount of data. Hackers always mark their presence on regular basis by hacking the website of police department and fetching the information from such platform is not a hard task for them (Ketchell, 2018). However, one has to evaluate and measure the pros and cons. On one hand, people are getting security from police department and the effectiveness of policing also increase by the implementation of AFRA. On the other hand, the system is putting their personal information under jeopardy. However, the issue can be resolved by taking proper measure. Making changes in the policy and law making process is not the only way of doing it. The police department and government should purchase the software from only kitemarked suppliers and keep update their platforms on regular basis (Azar&Brostoff,2014). Also, providing the access to the information to the very limited people can also be a positive step and effectively help in the implementation of AFRA for policing purposes.

6. Conclusion: On the use of Biometrics

In this paper, a thorough discussion on the use of biometrics in public working and policing process was carried out. Particularly, the automated facial recognition authentication system (AFRA) was elucidated. It was determined that there are many upsides along with some downsides of the system. It was identified that the system is very user friendly and time saving. People can make use of the system for applying for the licence for different purposes. In addition to this, the system also increases the security of applicant as the access lies to them only. But, some researcher criticises the current AFRA systems as they make the user’s information and person details vulnerable to cyber-attacks. In addition to this, the system’s application in the policing purposes was also elaborated and assessed. It was identified that it would increase the security of the town on one hand but simultaneously causes some ethical and privacy issues. People would lose their universal right to privacy and their information can be altered and can be used against them. However, to stop them, certain recommendations were also provided in order to use them for the great purpose as this technology has a great future in the upcoming year.

7. References

  • Azar, C., &Brostoff, G. (2014).  S. Patent No. 8,627,096. Washington, DC: U.S. Patent and Trademark Office.
  • De Marsico, M., Galdi, C., Nappi, M., &Riccio, D. (2014). Firme: Face and iris recognition for mobile engagement.  Image and Vision Computing,  32(12), 1161-1172.
  • Gonion, J., & Kerr, D. R. (2013).  S. Patent No. 8,600,120. Washington, DC: U.S. Patent and Trademark Office.
  • Azar, C., &Brostoff, G. (2013).  S. Patent No. 8,370,639. Washington, DC: U.S. Patent and Trademark Office.
  • Wickes, J. (2018). Automated facial recognition can benefit society – if we support its development properly - IFSEC Global | Security and Fire News and Resources. Retrieved 28 July 2019, from
  • Ohlyan, S., Sangwan, S., & Ahuja, T. (2013, June). A Survey On Various Problems & Challenges In Face Recognition. In  International Journal of Engineering Research & Technology (IJERT)(Vol. 2, No. 6).
  • Cardiff University. (2018). Evaluating the use of automated facial recognition technology in major policing operations. Retrieved 28 July 2019, from
  • Ketchell, M. (2018). Why regulating facial recognition technology is so problematic - and necessary. Retrieved 28 July 2019, from
  • Government Europa. (2018). Automated facial recognition technology wrong in 98% of cases, says new report. Retrieved 28 July 2019, from
  • Horikawa, M. (2019). Facial Recognition Has Arrived, but Its Flaws Remain. Retrieved 28 July 2019, from
  • Hanson, F. (2018). Time for an about-face? Flaws in facial recognition plan | The Strategist. Retrieved 28 July 2019, from
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