Introduction to FERET Database and Facial Recognition using Local Binary Patterns

Face recognition includes two basic testing procedures. It includes both facial identification and verification. Face identification involves the process of giving the unknown fresh face to the system and ask it if it can recognize the person from already available database (of multiple images) in the system. For verification purposes, biometric signatures are stored on smart card in advance before delivering those to the authenticated masses. These persons swipe their biometric card in the card reader and give system their fresh signature. Now, the system, in turn, will compare both the newly given signature by the claimed person with the signature stored in the biometric card. On the basis of the compared result, either the claimed person is considered authenticated or not

Combining multiple biometrics to protect privacy

As biometrics are gaining popularity, there is increased concern over the loss of privacy and potential misuse of biometric data held in central repositories. The association of fingerprints with criminals raises further concerns. On the other hand, the alternative suggestion of keeping biometric data in smart cards does not solve the problem, since forgers can always claim that their card is broken to avoid biometric verification altogether. We propose a biometric authentication framework which uses two separate biometric features combined to obtain a non-unique identifier of the individual, in order to address privacy concerns. As a particular example, we demonstrate a fingerprint verification system that uses two separate fingerprints of the same individual. A combined biometric ID composed of two fingerprints is stored in the central database and imprints from both fingers are required in the verification process, lowering the risk of misuse and privacy loss. We show that the system is successful in verifying a person’s identity given both fingerprints, while searching the combined fingerprint database using a single fingerprint, is impractical

Biometric system-on-card, standardization

A biometric system-on-card (BSoC) is a smartcard containing a complete set of biometric modules, from the data acquisition to the decision making. This technology is being standardized in the ISO/IEC 17839 series of standards in a modality independent way to allow in the future multiple biometric modalities available in the market

Smart Cards to Enhance Security and Privacy in Biometrics

Smart cards are portable secure devices designed to hold personal and service information for many kind of applications. Examples of the use of smart cards are cell phone user identification (e.g. GSM SIM card), banking cards (e.g. EMV credit/debit cards) or citizen cards. Smart cards and Biometrics can be used jointly in different kinds of scenarios. Being a secure portable device, smart cards can be used for storing securely biometric references (e.g. templates) of the cardholder, perform biometric operations such as the comparison of an external biometric sample with the on-card stored biometric reference, or even relate operations within the card to the correct execution and result of those biometric operations. In order to provide the reader of the book with an overview of this technology, this chapter provides a description of smart cards, from their origin till the current technology involved, focusing especially in the security services they provide. Once the technology and the security services are introduced, the chapter will detail how smart cards can be integrated in biometric systems, which will be summarized in four different strategies: Store-on-Card, On-Card Biometric Comparison, Work-sharing Mechanism, and System-on-Card. Also the way to evaluate the joint use of smart cards and Biometrics will be described; both at the performance level, as well as its security. Last, but not least, this chapter will illustrate the collaboration of both technologies by providing two examples of current major deployments.Publicad

Review of Multimodal Biometric Identification Using Hand Feature and Face

In the era of Information Technology, openness of the information is a major concern. As the confidentiality and integrity of the information is critically important, it has to be secured from unauthorized access. Security refers to prohibit some unauthorized persons from some important data or from some precious assets. So we need accurateness on automatic personal identification in various applications such as ATM, driving license, passports, citizen's card, cellular telephones, voter's ID card etc. Unimodal system carries some problems such as Noise in sensed data, Intra-class variations, Inter-class similarities, Non-universality and Spoof attacks. The accuracy of system is improved by combining different biometric traits which are called multimodal. This system gives more accuracy as it would be difficult for imposter to spoof multiple biometric traits simultaneously. This paper reviews different methods for fusion of biometric traits

Use of Multimodal Biometric System for the Authentication and Security

We know that security is the main challenge of the modern era, there may be many techniques and methods used for providing the security of any system or data. The biometric system is the widely used method for security. The biometric security is more secure method then others like passwords, card etc. In biometric the part of the body with some uniqueness use as the input image. But now a day the use of single biometric is not more secure, so the alternative or solution of this problem is to use the Multimodal biometric system. In a multimodal system more than one biometric trait used for providing security and authentication to a system. The images are stored in the database by using different operations on the images for compare it by input images. There are some steps used in processing of multimodal biometric system like as ROI, feature extraction and matching

Design of a secure unified e-payment system in Nigeria: A case study

The automatic teller machine (ATM) is the most widely used e-Payment instrument in Nigeria. It is responsible for about 89% (in volume) of all e-Payment instruments since 2006 to 2008. Some customers have at least two ATM cards depending on the number of accounts operated by them and they represent the active users of the ATM cards. Furthermore, identity theft has been identified as one of the most prominent problems hindering the wider adoption of e-Business, particularly e-Banking, hence the need for a more secure platform of operation. Therefore, in this paper we propose a unified (single) smart card-based ATM card with biometric-based cash dispenser for all banking transactions. This is to reduce the number of ATM cards carried by an individual and the biometric facility is to introduce another level of security in addition to the PIN which is currently being used. A set of questionnaire was designed to evaluate the acceptability of this concept among users and the architecture of the proposed system is presented

Biometric Verification System for Automated Teller Machine (ATM)

Biometric Verification System for Automated Teller Machine (ATM) will serve as an alternative for the current verification system that uses ATM card and personal identification number (PIN) to protect against fraud and effectively eliminating most common attempts to gain unauthorized access. With biometric technology, customer can gain access to their account through smart card approach combined with biometric technology to automatically identify individuals using their distinct physical or behavioral characteristics. The main objective of this project is to solve the problems that arise from using PIN as the base of ATM verification system. These include unauthorized access into financial accounts, stealing money, ATM fraud and many more. To ensure a reliable project output, the author had outlined the scope of study for the proposed project. It involves the study of ATM system, biometrics technology, architecture, the benefits and the drawback of each approach and the current trend in the market. The development of this system will be based on the RAD methodology