It is of great importance over a past few years, the increasing concern to preserve the privacy of biometric data over personal information that is stored in computer systems. It mostly has increased interest in data security. For possible use in biometric identification and protection, in this paper it applies visual cryptography(VC) which is a perfectly secured method of maintaining image security. The basic concept of visual cryptography is to divide secret images in to random shares using key and decryption is performed by superimposing the shares using the similar key which is used at encryption side. In this process it required special software for cryptographic computations and in this paper it is implemented using mat lab 7.9.A modified version of pixel sieve method is proposed in this paper for iris images to achieve more security than existing pixel sieve method. It is the modified version of pixel and is based on key shifting scheme. The simulations results show that the quality of the encrypted and decrypted images is better than existing pixel sieve method.
Wrongdoing at ATMs has turned into an issue across the country that appearances clients, as well as bank administrators and this money related wrongdoing case rise over and again as of late. A great deal of crooks mess with the ATM terminal and take clients' card points of interest by illicit means. When clients' bank card is lost and the secret key is stolen, the clients' record is helpless against assault. Conventional ATM frameworks confirm for the most part by utilizing a card (credit, charge, or brilliant) and a secret word or PIN which doubtlessly has a few imperfections. The predominant methods of client verification, which includes the utilization of either passwords, and client IDs (identifiers) or recognizable proof cards and PINs (individual distinguishing proof numbers), experience the ill effects of a few confinements. Passwords and PINs can be unlawfully obtained by direct incognito perception. At whatever point credit and ATM cards are lost or stolen, an unapproved customer can every now and again think about the right individual codes. An implanted unique mark and iris combined biometric validation plan for robotized teller machine (ATM) managing an account framework is proposed in this paper. In this plan, a multimodal biometric system is intertwined with the ATM for individual validation to ease the security level. The paper is masterminded as follows: Section 2 gives the back ground and literature survey of ATM security and the requirement for biometrics, and the related work on biometric identifiers. Section 3 depicts the materials and techniques utilized to direct the overview. Section 4 exhibits the outcomes got and the talks on the outcomes. Section 5 winds up with conclusions.
Security plays a very important role in one's life. Due to the limitations imposed by real time applications, its very challenging deal to get the accurate identification of the person to access secured application such as access to ATM, nuclear facilities, boarding a commercial flight or performing a remote financial transactions etc. Unimodal and multimodal are the two types of biometric systems. In these multimodal biometric systems are gaining more popularity as it is capable of addressing some of the challenges involved in designing of biometric systems such as non universality, noise in sensed data, susceptibility to spoof attacks. In this paper, we give a brief overview of security for multimodal biometrics for wireless images and its advantages, challenges, drawbacks and limitations. We also discuss the VLSI architecture for the Visual Cryptography (VC) for Multimodal Biometrics System (MMBS) of finger print and Iris images for ATM (Automatic Teller Machine).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.