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Reliability of biometric identification using fingerprints under adverse conditions
Abstract
Biometric user identification is highly topical these days. The most well-represented method is fingerprint identification, to which this study is also dedicated. However, we cannot forget other methods such as scanning the bloodstream, retina and iris, facial recognition, etc. Four reading devices were tested in this study. Tests were carried out both under standard and adverse conditions. Adverse conditions included situations such as cold finger, cooled damp finger, heated finger, soaked finger, finger with a layer of instant glue, and dirty finger (soil). All tests performed under adverse conditions simulated realistic industrial plant environments. The results of the measurements showed that the measured reliability values do not correspond to those claimed by the manufacturers. It is necessary to adapt and perfect these biometric identification systems for use in industrial areas, as they are often used in these areas as access or attendance systems.
... The environmental condition of the acquisition environment, such as the dirty fingerprint sensor area, extremely high temperatures, or unusual lightning can affect fingerprint image quality. Some of the more common conditions which were tested in the controlled environment are cold finger, cold-wet finger, heated finger, soaked finger, glued finger, and dirty finger [8]. The experiment [8] was conducted on four different fingerprint readers. ...
... Some of the more common conditions which were tested in the controlled environment are cold finger, cold-wet finger, heated finger, soaked finger, glued finger, and dirty finger [8]. The experiment [8] was conducted on four different fingerprint readers. There were 80 participants aged between 21 and 66 years old. ...
This paper presents a research study conducted in a specially developed laboratory for biometric engineering education. The laboratory gives students an opportunity to learn more about fingerprint acquisition and analyze the impact of acquisition on other parts of the biometric authentication process. An IoT approach was used, as different types of sensors (biometric sensors, thermometer, and humidity sensor) and components (heaters and workstations) were included in setting up a working surface for biometric data acquisition. Working surfaces create a network where data collected from each working station is recorded in a database. In parallel with biometric data acquisition, environmental condition parameters are recorded. Collected data is available to students for later analysis through the use of a specially developed visualization tool. In order to fully utilize the possibilities the laboratory provides, a flipped classroom approach was used. An evaluation study was done as a part of the course of Biometric technology held at the University of Belgrade. Research results show improvements in student learning outcomes and motivation.
Despite advancements made to improve the effectiveness and efficiency of access control mechanisms deployed in cyber-physical environments, their controlling logic-driven systems may remain heavily dependent on user interaction during the authentication process. In instances where elevated security requirements are warranted, the authentication methods may be multi-factored in nature, leading to bottlenecks that become more pronounced during peak traffic hours. Logical access control has considered location and time for authentication and re-authentication for some time now and context-driven authentication is fast becoming a standard feature of enterprise-class publicly available products and is used in financial technology (fintech), and eCommerce solutions. This paper focuses on the prototype implementation of context-driven authentication in a cyber-physical access control environment, deployed in a large organization that makes use of information typically collected in the course of the organization’s business operations to uphold security requirements while maintaining efficient access control.KeywordsContext-DrivenAuthenticationCyber-Physical SecurityAccess Control
The paper demonstrates a need to study the functional reliability of identification systems and the applicability of methods for ensuring the functional reliability of information systems for biometric identification systems. Methods of ensuring functional reliability of biometric identification systems via providing indicators of reliability of identification devices and introducing redundancy are considered. The applicability of the methods for biometric identification systems is investigated, its advantages and disadvantages are evaluated. Triple modular redundancy scheme has been developed for the program redundancy using N-version programming. An appropriate reliability scheme based on the principles of dual programming has been developed to implement the identification system with one additional redundant element. Based on the NIST statistics of face recognition algorithms for the developed reliability schemes the reliability indicators were evaluated and its advantages over a system consisting of a single non-redundant element have been shown. The proposed reliability schemes are consistent with the practice of ensuring the functional reliability of information systems and can be integrated into biometric identification systems that use biometric data as the main access identifier.
A new heuristic algorithm is presented in this study, back-tracking search algorithm (BSA), based multiple distributed generations (DGs) and shunt capacitor banks (SCBs) optimal placement and size with system reconfiguration, in Radial distribution systems (RDs). The active power losses minimization is the objective function. BSA is applied on IEEE 33 bus and IEEE 69 radial distribution systems at three different levels of load. To realize the proposed algorithm performance there are four scenarios of DGs, SCBs placement and reconfiguration are suggested. The results by the proposed algorithm are compared with other algorithms in the literature. The obtained results pretend the BSA effective and its potential in solving optimization problem.
The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has heightened the need for ensuring that these systems are not compromised. While several issues related to fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint obfuscation refers to the deliberate alteration of the fingerprint pattern by an individual for the purpose of masking his identity. Several cases of fingerprint obfuscation have been reported in the press. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this paper are: 1) compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS, 2) investigating the impact of fingerprint alteration on the accuracy of a commercial fingerprint matcher, 3) classifying the alterations into three major categories and suggesting possible countermeasures, 4) developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution, and 5) evaluating the proposed technique and the NFIQ algorithm on a large database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem.
The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.
Fingerprint verification is an important biometric technique for
personal identification. We describe the design and implementation of a
prototype automatic identity-authentication system that uses
fingerprints to authenticate the identity of an individual. We have
developed an improved minutiae-extraction algorithm that is faster and
more accurate than our earlier algorithm (1995). An alignment-based
minutiae-matching algorithm has been proposed. This algorithm is capable
of finding the correspondences between input minutiae and the stored
template without resorting to exhaustive search and has the ability to
compensate adaptively for the nonlinear deformations and inexact
transformations between an input and a template. To establish an
objective assessment of our system, both the Michigan State University
and the National Institute of Standards and Technology NIST 9
fingerprint data bases have been used to estimate the performance
numbers. The experimental results reveal that our system can achieve a
good performance on these data bases. We also have demonstrated that our
system satisfies the response-time requirement. A complete
authentication procedure, on average, takes about 1.4 seconds on a Sun
ULTRA I workstation (it is expected to run as fast or faster on a 200
HMz Pentium)