Debit card competition: signature versus pin

This article explores costs and benefits of two types of debit card authorization methods—signature and PIN (personal identification number)—for merchants, consumers, and financial institutions. It also considers competition between signature- and PIN-based debit cards in the United States and looks at Canada's predominant usage of PIN-based debit cards.Debit cards ; Payment systems

Biometric multimodal security simulation on schedule Ii controlled drug

The paper present a multimodal (multi biometrics) security system focusing on the implementation of fingerprint recognition and facial feature recognition to enhance the existing method of security using password or personal identification number (PIN). This project is operated through a personal computer where all the identification for fingerprint and facial feature are done by using specific software. Successful identification will send a signal through a serial communication circuit and open an application. In this project, the final application should be a cupboard that store and secure schedule II controlled drug in hospital. Due to some problem, the final application was replaced by using a light emitting diode (LED) simulation circuit

Enhancing the personal identification number input as a means of identification signature

The process of typing the personal identification number (PIN) can be broken down into quantifiable components, such as latency time, keypress force, keypress duration and keypress displacement which can be evaluated and used to verify the identity of a person. The keypress pattern is called the PIN signature. As the PIN signature is like the written signature that differs slightly with every execution, a neural-fuzzy application is devised to verify the PIN signature input against the reference profile

Pin signature verification using wavelet transform

The personal identification number signature (PIN signature) is a method of remembering and typing the PIN using the de facto standard numeric keypad format. The PIN signature affords a second level security in that it enhances the PIN with additional information on the user, i.e. the profile of its input. The PIN signature reference profile can be viewed as a signal vector and can thus be enhanced and verified as to its physiological characteristics using wavelet transform. The result of this analysis is presented

Hand Vein Based Personal Identification System

Personal Identification is necessary and useful to prevent crime in our society. Biometric traits extracted from hand image are more secure to use for identification compared to Personal Identification Number (PIN) because these features cannot be stolen. Developing an effective hand vein based personal identification system using robust feature with appropriate classifier is a serious task. Therefore this work incorporates new hand vein feature and two different classifiers to develop a personal identification system. Experiments were carried-out to affirm appropriateness of Support Vector Machine (SVM) and Euclidean Distance Measure (EDM) for the proposed system. The results obtained show that the proposed system give better result using SVM compared to EDM

Cheap and Easy PIN Entering Using Eye Gaze

PINs are one of the most popular methods to perform simple and fast user authentication.PIN stands for Personal Identification Number, which may have any number of digits or even letters.Nevertheless, 4-digit PIN is the most common and is used for instance in ATMs or cellular phones.The main advantage of the PIN is that it is easy to remember and fast to enter. There are, however,some drawbacks. One of them - addressed in this paper - is a possibility to steal PIN by a techniquecalled `shoulder surfing'. To avoid such problems a novel method of the PIN entering was proposed.Instead of using a numerical keyboard, the PIN may be entered by eye gazes, which is a hands-free,easy and robust technique

PIN generation using EEG : a stability study

In a previous study, it has been shown that brain activity, i.e. electroencephalogram (EEG) signals, can be used to generate personal identification number (PIN). The method was based on brain–computer interface (BCI) technology using a P300-based BCI approach and showed that a single-channel EEG was sufficient to generate PIN without any error for three subjects. The advantage of this method is obviously its better fraud resistance compared to conventional methods of PIN generation such as entering the numbers using a keypad. Here, we investigate the stability of these EEG signals when used with a neural network classifier, i.e. to investigate the changes in the performance of the method over time. Our results, based on recording conducted over a period of three months, indicate that a single channel is no longer sufficient and a multiple electrode configuration is necessary to maintain acceptable performances. Alternatively, a recording session to retrain the neural network classifier can be conducted on shorter intervals, though practically this might not be viable

STORED JOBS PIN REGENERATION

LaserJet printers provide different means of secure printing using smart cards, PIN (Personal Identification Number) etc. Print jobs secured with a PIN can be stored as a temporary or permanent file on the printer. With the current behavior on LaserJet Printers, if the user submits a PIN print job and forgets the pin, then the user can neither print the job nor delete the job. When the job resides as a permanent file, factory reset is only the option to remove the file from the printer. This paper presents a way to regenerate the PIN in a secure way to enable the user to retrieve the print file. This also reduces the need to factory reset to delete stored print files with forgotten PIN

Analysis of user behavior and authorization methods in context of mobile devices security

This article discusses authentication methods for users of mobile devices with touchscreens. The analysis concerns the authentication methods already existing in Android OS and new authorization methods proposed by the authors. Pattern and PIN (Personal Identification Number) lock were compared with two new authentication methods. The time required for entering the key, number of mistakes, number of possible combinations were analyzed