Biometrics and Fingerprint Payment Technology
Published on Jan 16, 2020
This article discusses biometric authentication in relation to payment systems. Biometrics uses biological traits or behavioural characteristics to identify an individual. A Biometrics system is effective pattern recognition system that utilizes different patterns similar to retina patterns, iris patterns and biological qualities like fingerprints, voice recognition, facial geometry and hand recognition etc. Biometric payment system is protected and sheltered and incredibly trouble-free to use and even without using password or top secret codes to keep in mind as compare with previous system like credit card payment system, and mobile banking etc. In daily life the usage of credit cards and debit card for shopping, bill payment, travelling and so on.
So problem is that a person has to remember their passwords or secret code and to keep secure to take with him all time. So biometric system will solve this problem. Greater implementation of biometric payment system is more reasonably priced to small business owners. We actually require alternate payment systems.
Biometrics is automated methods of recognizing a person based on a physiological or behavioral attribute. Along with the quality considered are; face, fingerprint, hand geometry, iris, retinal, signature, and voice. Biometric technologies are fetching the establishment of an extensive array of extremely safe recognition and personal authentication solutions. As the level of security breaches and transaction fraud increases, the need for highly secure identification and personal verification technologies is becoming apparent. Biometric-based solutions are proficient to offer for confidential financial transactions and personal data privacy. The need for biometrics can be found in federal, state and local governments, in the military, and in commercial applications.
Enterprisewide network security infrastructures, government IDs, secure electronic banking, investing and other financial transactions, retail sales, law enforcement, and health and social services are already benefiting from these technologies. Biometric-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security. Trust in these electronic transactions is essential to the healthy growth of the global economy.
Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives. Utilizing biometrics for personal authentication is becoming convenient and considerably more accurate than current methods (such as the utilization of passwords or PINs). This is because biometrics links the event to a particular individual (a password or token may be used by someone other than the authorized user), is convenient (nothing to carry or remember), accurate (it provides for positive authentication), can provide an audit trail and is becoming socially acceptable and inexpensive.
Fingerprint looks at the patterns found on a fingertip. There are a variety of approaches to fingerprint verification. Some emulate the traditional police method of matching minutiae; others use straight pattern-matching devices; and still others are a bit more unique, including things like patterns and ultrasonic. Some verification approaches can detect when a live finger is presented; some cannot. A greater variety of fingerprint devices is available than for any other biometric. As the prices of these devices and processing costs fall, using fingerprints for user verification is gaining acceptance — despite the common — criminal stigma. Fingerprint verification may be a good choice for in-house systems, where you can give users adequate explanation and training, and where the system operates in a controlled environment. It is not surprising that the workstation access application area seems to be based almost exclusively on fingerprints, due to the relatively low cost, small size, and ease of integration of fingerprint authentication devices.
Hand Geometry involves analyzing and measuring the shape of the hand. This biometric offer a good balances of performance characteristics and is relatively easy to use. It might be suitable where there are more users or where users access the system infrequently and are perhaps less disciplined in their approach to the system. Accuracy can be very high if desired and flexible performance tuning and configuration can accommodate a wide range of applications. Organizations are using hand geometry readers in various scenarios, including time and attendance recording, where they have proved extremely popular. Ease of integration into other systems and processes, coupled with ease of use, and makes hand geometry an obvious first step for many biometric projects.
Iris based biometric, on the other hand, involves analyzing features found in the colored ring of tissue that surrounds the pupil. Iris scanning, undoubtedly the less intrusive of the eyerelated biometrics, uses a fairly conventional camera element and requires no close contact between the user and the reader. In addition, it has the potential for higher than average templatematching performance. Iris biometrics work with glasses in place and is one of the few devices that can work well in identification mode. Ease of use and system integration have not traditionally been strong points with iris scanning devices, but you can expect improvements in these areas as new products emerge. 5. Retina Retina based biometric involves analyzing the layer of blood vessels situated at the back of the eye. An established technology, this technique involves using a low-intensity light source through an optical coupler to scan the unique patterns of the retina. Retinal scanning can be quite accurate but does require the user to look into a receptacle and focus on a given point. This is not particularly convenient if you wear glasses or are concerned about having close contact with the reading device. For these reasons, retinal scanning is not warmly accepted by all users, even though the technology itself can work well.
Signature verification analyzes the way a user signs her name. Signing features such as speed, velocity, and pressure are as important as the finished signature’s static shape. Signature verification enjoys a synergy with existing processes that other biometrics do not. People are used to signatures as a means of transaction-related identity verification, and most would see nothing unusual in extending this to encompass biometrics. Signature verification devices are reasonably accurate in operation and obviously lend themselves to applications where a signature is an accepted identifier. Surprisingly, relatively few significant signature applications have emerged compared with other biometric methodologies. But if your application fits, it is a technology worth considering.
Voice authentication is not based on voice recognition but on voiceto- print authentication, where complex technology transforms voice into text. Voice biometrics has the most potential for growth, because it requires no new hardware — most PCs already contain a microphone. However, poor quality and ambient noise can affect verification. In addition, the enrollment procedure has often been more complicated than with other biometrics, leading to the perception that voice verification is not user friendly. Therefore, voice authentication software needs improvement. One day, voice may become an additive technology to finger-scan technology. Because many people see finger scanning as a higher authentication form, voice biometrics will most likely be relegated to replacing or enhancing PINs, passwords, or account names.
The acquisition of fingerprint images has been historically carried out by spreading the finger with ink and pressing it against a paper card. The paper card is then scanned, resulting in a digital representation. This process is known as off-line acquisition and is still used in law enforcement applications. Currently, it is possible to acquire fingerprint images by pressing the finger against the flat surface of an electronic fingerprint sensor. This process is known as online acquisition.
There are three families of electronic fingerprint sensors based on the sensing technology
• Solid-state or silicon sensors (left part of Fig.4.2):
These consist of an array of pixels, each pixel being a sensor itself. Users place the finger on the surface of the silicon, and four techniques are typically used to convert the ridge/valley information into an electrical signal: capacitive, thermal, electric field and piezoelectric. Since solid-state sensors do not use optical components, their size is considerably smaller and can be easily embedded. On the other hand, silicon sensors are expensive, so the sensing area of solidstate sensors is typically small.
• Optical (right part of Fig.4.2):
The finger touches a glass prism and the prism is illuminated with diffused light. The light is reflected at the valleys and absorbed at the ridges. The reflected light is focused onto a CCD or CMOS sensor. Optical fingerprint sensors provide good image quality and large sensing area but they cannot be miniaturized because as the distance between the prism and the image sensor is reduced, more optical distortion is introduced in the acquired image.
Acoustic signals are sent, capturing the echo signals that are reflected at the fingerprint surface. Acoustic signals are able to cross dirt and oil that may be present in the finger, thus giving good quality images. On the other hand, ultrasound scanners are large and expensive, and take some seconds to acquire an image. A new generation of touch less live scan devices that generate a 3D representation of fingerprints is appearing . Several images of the finger are acquired from different views using a multi camera system, and a contact-free 3D representation of the fingerprint is constructed. This new sensing technology overcomes some of the problems that intrinsically appear in contact-based sensors such as improper finger placement, skin deformation, sensor noise or dirt.
Biometrics is a means of verifying personal identity by measuring and analyzing unique physical or behavioural characteristics like fingerprints or voice patterns. The conclusion of this whole paper is that the card-less payment system should be replaced and there must be more easier, reliable, secure, cash free and tension free payment system, i-e biometric payment system in which no body have to take with dozens of cards for shopping, travelling, pass in office, university or bank as door lock. And the International Journal of Advanced Science and Technology Vol. 4, March, 2009 36 must have some secure codes to access as authorization and there is also one another disadvantage is that there may be stolen of cards or it can be losses at any time without any care.
So to consider all these kinds of problems and disadvantages of card payment system the fingerprints payment system is suggested to be implemented because it is easier, reliable, feasible, secure and easily authorized to everyone. And there is no any worry that anyone can stolen my finger are can be loosed anywhere so other body can use it. In fingerprint payment system customer has to place his fingers on the finger scanner and then scanner will recognize the account which belongs to that person and charge the bill. So it is easy for both customer and seller because there is no need to scratch the credit card and then enter code if code is forgot or if some time card cannot read and many more problems can occur in card payment system.
And in biometric payment system no need to carry cash with them. Biometric payment system may be like fingerprints, IRIS, face recognition and blood reading or skin reading and it may be installed at any store, university, library, hostel, bank, office, home door lock, internet online shopping and many kinds where card system is installed. So in this paper we explain the biometrics with detailed term, how fingerprint system works, fingerprints’ types and fingerprint recognition through circular sampling.
Paper Published by S.Padma Priya, Department of Information Technology, Sri Adi Chunchanagiri Women’s College, Cumbum
 T. F. Lunt, A. Tamaru, F. Gilham, R. Jagannathan, P. G. Neumann, H. S. Javitz, A. Valdes, and T. D. Garvey. AReal-Time Intrusion Detection Expert System (IDES) - Final Technical Report. Technical report, SRI Computer Science Laboratory, SRI International, Menlo Park, CA, Feb. 1992.
 Dr. Yashpal Singh and Singh Chauhan, Neural networks in data mining. Journal of Theoretical and Applied Information Technology (2005-2009), vol, 5, no. 6. pp. 37-42.
 Khyati Chaudhary, Jyoti Yadav and Bhawna Mallick, A review of fraud detection techniques: credit-card, International Journal of Computer Applications (2012), vol. 45, no. I, pp.39-44
 Cybercrime: protecting against the growing threat Global Economic Crime Survey – PWC Global Economic. [ONLINE]. Available at: http://www.pwc.com/en_GX/gx/ economic-crime-survey/assets/GECS_GLOBAL_REPORT. pdf. [Accessed 12 December 2012].
 S. Rosset, U. Murad., E. Neumann, Y. Idan, and G. Pinkas. Discovery of fraud rules for telecommunicationslchallenges and solutions. In Proceedings of the fifth ACM SlGKDDinternational conference on Knowledge discovery and data mining, pages 409-413. ACM Press,1999.