4,604 research outputs found
On the Feasibility of Creating Double-Identity Fingerprints
A double-identity fingerprint is a fake fingerprint created by combining features from two different fingers, so that it has a high chance to be falsely matched with fingerprints from both fingers. This paper studies the feasibility of creating double-identity fingerprints by proposing two possible techniques and evaluating to what extent they may be used to fool the state-of-the-art fingerprint recognition systems. The results of systematic experiments suggest that existing algorithms are highly vulnerable to this specific attack (about 90% chance of success at FAR = 0.1%) and that the fingerprint patterns generated might be realistic enough to fool human examiners
Detecting Double-Identity Fingerprint Attacks
Double-identity biometrics, that is the combination of two subjects features into a single template, was demonstrated to be a serious threat against existing biometric systems. In fact, well-synthetized samples can fool state-of-the-art biometric verification systems, leading them to falsely accept both the contributing subjects. This work proposes one of the first techniques to defy existing double-identity fingerprint attacks. The proposed approach inspects the regions where the two aligned fingerprints overlap but minutiae cannot be consistently paired. If the quality of these regions is good enough to minimize the risk of false or miss minutiae detection, then the alarm score is increased. Experimental results carried out on two fingerprint databases, with two different techniques to generate double-identity fingerprints, validate the effectiveness of the proposed approach
ATM & Biometric Solutions: A Case Study
The paper highlights security features for biometric systems along with application specific to a bank in Pakistan. Further, a comprehensive view of retinal scanning and application within the Internet of Things (IoT) paradigm is discussed. Of the various forms of scanning techniques, fingerprint, iris, and facial have been selected as a security measure. However, the application of retinal scans for security within ATMs in Pakistan is novel. Retinal scans face many issues such as external pressures that can make the implementation of retinal scans difficult, proper technological advancements for implementing of retinal scans, costing and whether it will serve as a barrier and whether the overall concept of implementing retinal scans is a workable idea or not. The sample taken was of 80 close ended questionnaires filled along with 4 focus group discussions. The questions related to technology, economics and situational awareness concepts. The concept of automated houses and the use of objects with artificial intelligence were of special interest. It is shown that  external factors especially cost and technological limitations prohibit widespread adoption of biometric based retinal scans and implications for overall privacy and security that is present
Fingerprint Recognition System(FRS) for the Perak Loan/Scholarship System
Creating a biometric verification system in an energy and area constrained
embedded environment is a challenging problem. This paper gives results for using
triangulation process to improve performance ofminutiae matching. Triangulation
process is the process of aligning the two fingerprints and compares the fingerprint
minutiae with minutiae in the database. Human has almost 50 minutiae in their
fingerprints. The fingerprint recognition system (FRS) will test the fingerprint and
allows the Perak Loan/Scholarship system tobe access when 13 minutiae match with
the stored fingerprint data. However, as many data in the database, there are problems
ofacquiring the data. The time taken to retrieve data may increase due to this large
volume ofdata stored. In a real apphcation, the sensor, the acquisition system and the
variation in performance ofthe system over time is very critical. Therefore the system
improves the minutiae matching performance by achieving data retrieving in within 3
seconds. Aset of30 fingerprints from 10 individuals were used totest the system. As
the result of the proposed approach, the author achieved 2.68 seconds of average
fingerprint matching time and 80% ofcorrect fingerprint matching accuracy for FRS
Strengthening e-banking security using keystroke dynamics
This paper investigates keystroke dynamics and its possible use as a tool to prevent or detect fraud in the banking industry. Given that banks are constantly on the lookout for improved methods to address the menace of fraud, the paper sets out to review keystroke dynamics, its advantages, disadvantages and potential for improving the security of e-banking systems. This paper evaluates keystroke dynamics suitability of use for enhancing security in the banking sector. Results from the literature review found that keystroke dynamics can offer impressive accuracy rates for user identification. Low costs of deployment and minimal change to users modus operandi make this technology an attractive investment for banks. The paper goes on to argue that although this behavioural biometric may not be suitable as a primary method of authentication, it can be used as a secondary or tertiary method to complement existing authentication systems
On Generative Adversarial Network Based Synthetic Iris Presentation Attack And Its Detection
Human iris is considered a reliable and accurate modality for biometric recognition due to its unique texture information. Reliability and accuracy of iris biometric modality have prompted its large-scale deployment for critical applications such as border control and national identification projects. The extensive growth of iris recognition systems has raised apprehensions about the susceptibility of these systems to various presentation attacks.
In this thesis, a novel iris presentation attack using deep learning based synthetically generated iris images is presented. Utilizing the generative capability of deep convolutional generative adversarial networks and iris quality metrics, a new framework, named as iDCGAN is proposed for creating realistic appearing synthetic iris images. In-depth analysis is performed using quality score distributions of real and synthetically generated iris images to understand the effectiveness of the proposed approach. We also demonstrate that synthetically generated iris images can be used to attack existing iris recognition systems.
As synthetically generated iris images can be effectively deployed in iris presentation attacks, it is important to develop accurate iris presentation attack detection algorithms which can distinguish such synthetic iris images from real iris images. For this purpose, a novel structural and textural feature-based iris presentation attack detection framework (DESIST) is proposed. The key emphasis of DESIST is on developing a unified framework for detecting a medley of iris presentation attacks, including synthetic iris. Experimental evaluations showcase the efficacy of the proposed DESIST framework in detecting synthetic iris presentation attacks
EU Borders and Their Controls: Preventing unwanted movement of people in Europe? CEPS Essay No. 6, 14 November 2013
his Essay attempts to take a step back from the tragic event in the first week of October 2013, when a boat capsized off the Italian island of Lampedusa and some 300 persons drowned seeking safe harbour. It sets out to examine the issue of EU border controls from the perspectives of the technologies, new and old, building on a variety of scholarly disciplines to understand what is happening to border controls on the movement of persons in the EU and why the results are so deadly.
The Essay opens with an overview of what actually happens at the EU’s external borders. It then moves on to assess the old and new set of border control technologies that are deployed at the EU external borders, and how new technologies such as those based on automated controls and biometrics, are transforming the classical principles of European border controls. It then covers the reasons why people are refused admission at the EU’s external borders and the extent to which new border and surveillance technologies would assist in the effective controls in light of EU border law. Conclusions are finally offered on the articulation between the facts of EU border controls on persons and the claims and proposals for new technologies that are emerging from the EU institutions
Deep Learning based Fingerprint Presentation Attack Detection: A Comprehensive Survey
The vulnerabilities of fingerprint authentication systems have raised
security concerns when adapting them to highly secure access-control
applications. Therefore, Fingerprint Presentation Attack Detection (FPAD)
methods are essential for ensuring reliable fingerprint authentication. Owing
to the lack of generation capacity of traditional handcrafted based approaches,
deep learning-based FPAD has become mainstream and has achieved remarkable
performance in the past decade. Existing reviews have focused more on
hand-cratfed rather than deep learning-based methods, which are outdated. To
stimulate future research, we will concentrate only on recent
deep-learning-based FPAD methods. In this paper, we first briefly introduce the
most common Presentation Attack Instruments (PAIs) and publicly available
fingerprint Presentation Attack (PA) datasets. We then describe the existing
deep-learning FPAD by categorizing them into contact, contactless, and
smartphone-based approaches. Finally, we conclude the paper by discussing the
open challenges at the current stage and emphasizing the potential future
perspective.Comment: 29 pages, submitted to ACM computing survey journa
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