Current Situations in Innovation and Technology of Biometrics
Opportunities and Future of Biometrics
Currently, biometrics is used in many systems and applications in technical, scientific, engineering, and social challenges fields. Recently, there have many successful biometric systems. These include the hand geometry systems which are used to control access to premises such power plants, offices, factories, and campuses. Automated fingerprint identification systems (AFISs) are used to integrate automatic and manual processes in civilian and criminal applications (National Research Council, 2010). Despite this success, biometrics have been faced with challenges of being subjected to unrealistic expectations. Simply, individuals always want this systems to be 100% secure, which is impossible. In practice, however, a system need not be perfect; rather, it must have satisfactory performance. Due to the inherent vulnerability of most biometric systems, which is attributed to a combination of having high error rate, weaknesses in robustness, and system securities, they have not been effectively applied over a huge population.
Although current developments on biometrics has proved to have significant benefits to the society in general, overall, the biometric system is prone to attach, In particular, the system can be improved by enhancing research on some of its weaknesses. Research indicates that this field can be improved through better scientific interpretations on human factors, solving modality-related challenges, understanding the underlying phenomena, and checking on statistical engineering aspects of various activities (National Research Council, 2010).
Vulnerabilities of Biometric Systems
Abdullayeva, Imamverdiyev, Musayev, & Wayman (2009).
- Presenting fake sample
- Replay of stored digital biometric signal
- Denial of feature extraction
- Spoofing of biometric feature
- Attacking matching module
- Spoofing templates in database
- Attacking channel between the template and database and matching module
- Attacking the final decision process
Human Factors and Affordance
One important aspect of biometric recognition process is the input of human characteristics. This information is essential since biometric systems are mainly used for human recognition; therefore, the understanding of the interface through which they operate is essential in making them more efficient (National Research Council, 2010). In particular, very little effort has been put into ensuring that biometric systems are affordable to most of the public.
Quality is another essential character of the human factors that surround these systems. Basically, the quality of the data collected and stored into these systems is assumed to match. In this case, such information enables the information in the data to be tightly linked with individuals. Since system operators, just like other individuals are subject to human error, these individuals face challenges of human error when interfacing with the system (Sullivan, 2011). In particular, they are subject of human bias when establishing when and how to collect proper images, recognize quality of images, and in ensuring the data has been properly preserved.
Distinctiveness and Stability of Biometric Systems
There has been a lot of questioning on the character of the information collected and stored in biometric systems. This information primarily revolves on the distinctiveness of biometric information. In this case, scientific studies have not yet concluded that individual information in biometric systems is usually unique, and can be sustainably relied on (Sullivan, 2011). Further, depending on the unique biometric information captured, the changes in the physical traits of a person over time may affect the ability of these systems to correctly identify individuals.
Modality Related Research
All biometric systems rely on one or more biometric modalities. Generally, the choice of the modality in use significantly determines the structure of the system and how information is presented to users. Similarly, it also establishes how match and non-match decisions are made in the biometric system. Facial recognition should be able to be distinguish the surrounding environement (Sullivan, 2011). Additionally, biometric systems must be able to capture variant representations depending on changes in individuals’ expressions, poses, and also in different illuminations (National Research Council, 2010). In fingerprint readers, the main concern normally entails reducing the failure to acquire (FTA) or failure to enroll (FTE) rates. Typically, engineers attempt to develop machines that have better sensors, those that can capture better images, and also those with high resolution cameras (Sullivan, 2011). In iris recognition systems, the primary research opportunities are in the optimization of illumination spectrum, reduction of the FTE and FTA rates, reduction in size of hardware, and enhanced ability to read the iris from greater distances.
Information Security Research
Normally, biometric systems usually pose the challenge of: providing security for information systems, and determining the security, reliability, and integrity of the system (Sullivan, 2011). In the first challenge, it shows that biometric systems can be misleading when information in their database becomes corrupted (National Research Council, 2010). Accordingly, there is need for detailed security research to prevent attacks on the biometric systems, so that they can always replay the previously captured information, and also properly conceal this data.
Current Research Program
Although the existing biometric systems are more advanced than those that existed in the yesteryears, they are still not 100% efficient. In part, their ineffectiveness is due to their inherent problems due to the fact that they also require some level of human input, and that machines are prone to failure. Currently, most research on biometric systems aims at eliminating the existing challenges that are present in the existing equipment. One company that has been in the front line in ensuring that biometric systems are more effective is Hitachi.
The current use of biometrics has been important in enabling users to access their information easily and safely. At present, most individuals have between 25 and 50 passwords, which is extremely difficult for a user to recall. Unfortunately, not all biometric systems are full proof. For example, many iris scanner and fingerprint readers can be hacked using just two-dimensional photographs. More advanced systems require individuals to have three-dimensional images. At the moment, the Hitachi Digital Security solution set, appears to be 100 percent secure. Hitachi’s system is usually connected to readers that use near-infrared rays to see the image of a user’s vein pattern (Dolamore, 2017). Furthermore, the readers only authenticate fingers of people who are alive (Dolamore, 2017). Consequently, this system is extremely difficult to steal. In this regard, the vein authentication system is viewed as been very secure and accurate, and also more inclusive with regards to people who can use it.
In addition to the contemporary biometric systems, recent advancement in technology have led to the emergence of biological implants. In Sweden for example, one Swedish rail company currently offers its clients the option of using implants into their hands instead of using paper train tickets (Coffey, 2017). This tiny chips use the near field communication technology, which enables passengers to pay their fares by simply passing their hands over a scanner. In the same vein, the Wisconsin vending machine company is pioneering the wireless payment of snacks in it machines. In 2017, the company launched a test program using fifty employees to observe the effectiveness of the wireless payment, which is also done by customers’ passing their hands over a scanner (Darrow, 2017).
Usefulness of Biometric Systems
Typically, biometric systems are used in monitoring physical access entry, regulating time attendance, logical access control, surveillance, and in law enforcement. The use of biometric systems has significant advantages over other traditional passwords in the following ways:
- Platforms that use biometrics enable a person to easily log into a network using a shorter period than passwords.
- It is difficult to steal most biometric information, which makes these systems difficult to hack.
- The use of biometrics enables organization to reduce the cost of resetting passwords (Cook, Augusto, & Jakkula, 2007).
In physical access control, biometric systems are used to give or deny entry to various individuals. Traditionally, people used to have keys and budges, unfortunately, these systems were ineffective since these items could easily be copied or duplicated. Finger print recognition and hand geometry recognition are the most commonly used in this systems. Some companies have also installed vein pattern recognition to make these systems more tamper-proof. In most of these instances, the biometric readers are usually connected to an electromagnetic lock strike that opens after confirmation of an individual’s identity. One of the main advantage of this system is that it eliminates cases of lost or stolen identity cards. Additionally, it ensures that only individuals who have been fully identified are able to access secure premises.
The time and attendance function of biometric systems mostly occurs in factories. This system ensure that individuals’ clock-in time to work and when they leave is accurately recorded. The main advantage of this system is that it eliminates cases of “buddy punching” since workers have to physically clock in and out (Cook, Augusto, & Jakkula, 2007). Further, since the information is always digitally recorded, it enable timely recording and verification of data. Finally, this system enables an almost 100% automation of the human resource department, especially with regards to calculation of remuneration
Biometric systems are also very effective in the application of logical access control. In contemporary systems, passwords and usernames were mainly used in computers. Unfortunately, these security methods were prone to cyber-attacks, especially when a hacker user dictionary style or denial of service attacks. To overcome this challenge, most organizations require their employees to use long and complex passwords, and to regularly change these logins. While these measures are appropriate, they unfortunately make it very difficult for employees to recall their logins. Alternatively, employees write these passwords in books or on their desks, which comprises the required security measures (Cook, Augusto, & Jakkula, 2007). To overcome these challenge, most organizations have introduced biometric security measures. Importantly, biometrics enable employees to access the network quickly. Also, these system is more secure since it is extremely difficult to steal a person’s physiological and behavioral traits. Finally, organizations are usually able to avoid the financial cost of retrieving passwords.
A combination of various biometric tools are used to survey individuals, primarily with an aim of identifying criminals. In this system, the modality is deployed in CCTV cameras where it is used to identify known criminals or suspects. The most common forms of surveillance are overt surveillance, covert surveillance, tracking of individuals in watch lists, tacking of persons with suspicious behaviors, and tracking of people who have suspicious activities. In overt surveillance, the public is usually aware that it is being watched. In covert surveillance, individuals usually do not know that are being observed (Abdullayeva, Imamverdiyev, Musayev, & Wayman, 2009). The tracking of individuals on a watch lists is usually done with an objective of identifying a confirmed criminal. The tracking of individuals for suspicious behavior is usually a macro type surveillance that aims at identifying potential criminals. Finally, the tracking of individuals for suspicious activities normally uses CCTV cameras and facial recognition systems to track persons who are involved in criminal activities.
Biometric systems are also used in law enforcement. The most popular method is the fingerprint recognition technique. Additionally, international organizations also use iris, facial, as well as vein pattern recognition systems. Currently, most security organizations have databases that have the biometric identity of criminals. INTERPOL for example, has data of more than 55 million criminals. Therefore, biometric data of suspects is usually quickly searched in these data bases and used to verify if these persons are the criminals being searched.
Cultural Impact of Biometrics
Cross cultural attitudinal differences determine how people in different world regions adopt various biometric systems. In more conservative cultures, biometrics are viewed as been too intrusive, and even going against a communities norms (Cook, Augusto, & Jakkula, 2007). For example, in ultra conservative Jewish communities, alteration of a person’s body is unacceptable. Therefore, these communities are usually against biometric implants as they are viewed as being too intrusive.
The intrusive nature of biometrics also affects how different societies accept various biometric technologies. Normally, biometric systems are usually intrusive since they have personal information about an individuals. Therefore, in communities where people are reserved, and highly cherish their privacy, there is usually a low acceptance of these systems. In South Korea for example, most people quickly accept the loss of their privacy, which has enabled the country to establish biometric systems much easily.
Finally, although biometrics systems are able to easily capture and retrieve biometric information, these applications have led to the establishment of a culture of isolation. In this case, most individuals tend to spend a lot of their time privately since they can access privately access what they want (Cook, Augusto, & Jakkula, 2007). Accordingly, the presence of biometrics has led to a reduction in human socialization and interactions.
In conclusion, although biometric systems have enabled individuals to enhance their security systems, these tools are not 100% effective. A combination of both traditional and these continuous monitoring of biometric equipment is needed in ensuring that data contained in these systems is accurate, and can be relied in various biometric activities. With the current advancement and embracement of technology by most societies, the current biometric equipment will continue to improve so they can reduce the inherent vulnerabilities that are found in all of them.
Abdullayeva, F., Imamverdiyev, Y., Musayev, V., & Wayman, J. (2009). Analysis of security vulnerabilities in biometric systems. San Jose, CA: Institute of Information Technology of ANAS. Retrieved from https://danishbiometrics.files.wordpress.com/2009/08/1-13.pdf
Cook, D., Augusto, J., & Jakkula, V. (2007). Ambient intelligence: Technologies, applications, and opportunities. Pullma, WA: Washing State University.
Coffey, H. (2017). The future is here – a Swedish rail company is trialling letting passengers use biometric chips as tickets. Independent. Retrieved from http://www.independent.co.uk/travel/news-and-advice/sj-rail-train-tickets-hand-implant-microchip-biometric-sweden-a7793641.html.
Darrow, B. (2017). ‘Ick Factor’ and biometrics limit market for implanted security chips. Retrieved from http://fortune.com/2017/08/02/implanted-chips-vs-biometrics/.
Dolamore, K. (2017). Can biometric technology make our society more secure? The Telegraph. Retrieved from http://www.telegraph.co.uk/business/social-innovation/biometric-technology/.
National Research Council. (2010). Biometric recognition. Challenges and Opportunities. Washington, DC: The National Academies Press. https://doi.org/10.17226/12720.
Sullivan, C. (2011). Digital identity-Inherent vulnerabilities. JSTOR, 1-13.