Dynamic Biometric Signature - an Effective Alternative for Electronic Authentication

The use of dynamic biometric methods for the authentication of people provides significantly greater security than the use of the static ones. The variance of individual dynamic properties of a person, which protects biometric methods against attacks, can be the weak point of these methods at the same time.This paper summarizes the results of a long-term research, which shows that a DBS demonstrates practically absolute resistance to forging and that the stability of signatures provided by test subjects in various situations is high. Factors such as alcohol and stress have no influence on signature stability, either. The results of the experiments showed that the handwritten signature obtained through long practice and the consolidation of the dynamic stereotype, is so automated and stored so deep in the human brain, that its involuntary performance also allows other processes to take place in the cerebral cortex. The dynamic stereotype is composed of psychological, anatomical and motor characteristics of each person. It was also proven to be true that the use of different devices did not have a major impact on the stability of signatures, which is of importance in the case of a blanket deployment.The carried out experiments conclusively showed that the aspects that could have an impact on the stability of a signature did not manifest themselves in such a way that we could not trust these methods even used on commercially available devices. In the conclusion of the paper, the possible directions of research are suggested

Dynamic Biometric Signature - an Effective Alternative for Electronic Authentication

The use of dynamic biometric methods for the authentication of people provides significantly greater security than the use of the static ones. The variance of individual dynamic properties of a person, which protects biometric methods against attacks, can be the weak point of these methods at the same time. This paper summarizes the results of a long-term research, which shows that a DBS demonstrates practically absolute resistance to forging and that the stability of signatures provided by test subjects in various situations is high. Factors such as alcohol and stress have no influence on signature stability, either. The results of the experiments showed that the handwritten signature obtained through long practice and the consolidation of the dynamic stereotype, is so automated and stored so deep in the human brain, that its involuntary performance also allows other processes to take place in the cerebral cortex. The dynamic stereotype is composed of psychological, anatomical and motor characteristics of each person. It was also proven to be true that the use of different devices did not have a major impact on the stability of signatures, which is of importance in the case of a blanket deployment. The carried out experiments conclusively showed that the aspects that could have an impact on the stability of a signature did not manifest themselves in such a way that we could not trust these methods even used on commercially available devices. In the conclusion of the paper, the possible directions of research are suggested

Design and fabrication of electrostatic actuators with corrugated membranes for MEMS deformable mirror in space

A novel Microelectromechanical Systems (MEMS) deformable mirror (DM) technology for large, light weight, segmented space telescopes is being proposed. This technology is reported to provide an unprecedented imaging capability in a visible and near infrared spectral range. The MEMS-DM proposed in this paper consists of a continuous membrane mirror supported by electrostatic actuators with pixel-to-pixel spacing as small as 200 micrometer. An array of 4 X 4 electrostatic actuators for the DM has been successfully fabricated by a new membrane transfer technique. The fabricated actuator membrane has been characterized by using an optical surface profiler. The actuator shows a vertical deflection of 0.37 micrometer at 55 V. This device can also address requirements for smaller size and high resolution applications involving optical transmission through aberrating mediums such as imaging and optical communications through atmospheres, high resolution biometric retina signatures through the eye and endoscopic investigation of tissues and organs

Physiological signals: The next generation authentication and identification methods!?

Throughout the last 40 years, the security breach caused by human error is often disregarded. To relief the latter problem, this article introduces a new class of biometrics that is founded on processing physiological personal features, as opposed to physical and behavioral features. After an introduction on authentication, physiological signals are discussed, including their advantages, disadvantages, and initial directives for obtaining them. This new class of authentication methods can increase biometrics’ robustness and enables cross validation. I close this article with a brief discussion in which a recap of the article is provided, law, privacy, and ethical issues are discussed, some suggestions for the processing pipeline of this new class of authentication methods are done, and conclusions are drawn

The Effects of a Brief Yoga Intervention on Psychologic and Physiologic Measures in Women Recovering from Substance Abuse Disorders

Women are the fastest-growing population experiencing substance use disorders (SUDs) in the United States. Multiple barriers e.g., mental health disorders, reduced self-efficacy, lack of social support have been identified and negatively impact acute and sustainable recovery efforts. The aim of this project was to evaluate the effects of yoga on mood status, biometrics, and self-efficacy toward yoga in a cohort at The Next Door, a substance abuse treatment center for women only. This was a quasi-experimental research approach with 14 women completing a total of 8 weekly yoga sessions over a ten-week period. Appropriate demographic data was collected. Measurements were obtained with a pretest/posttest method using validated tools. All participants reported co-occurring mental health disorders and addiction to alcohol, illicit drugs, or both. Statistically significant improvements were noted in mood status, self-efficacy, and diastolic blood pressure measurements. Findings from this project substantiate results from similar studies and may offer insight into future research. Improving mood states and self-efficacy through yoga addresses identified barriers to treatment and may promote sustainable recovery efforts. More research is needed to identify which yoga parameters are most beneficial for this population e.g., phase of recovery, frequency of participation, type of yoga practice. Keywords: women, addiction, recovery, yoga, barriers, depression, anxiety, self-efficac

Beyond Biometrics

Throughout the last 40 years, the essence of automated identification of users has remained the same. In this article, a new class of biometrics is proposed that is founded on processing biosignals, as opposed to images. After a brief introduction on biometrics, biosignals are discussed, including their advantages, disadvantages, and guidelines for obtaining them. This new class of biometrics increases biometrics’ robustness and enables cross validation. Next, biosignals’ use is illustrated by two biosignal-based biometrics: voice identification and handwriting recognition. Additionally, the concept of a digital human model is introduced. Last, some issues will be touched upon that will arise when biosignal-based biometrics are brought to practice

Transcending conventional biometry frontiers: Diffusive Dynamics PPG Biometry

In the first half of the 20th century, a first pulse oximeter was available to measure blood flow changes in the peripheral vascular net. However, it was not until recent times the PhotoPlethysmoGraphic (PPG) signal used to monitor many physiological parameters in clinical environments. Over the last decade, its use has extended to the area of biometrics, with different methods that allow the extraction of characteristic features of each individual from the PPG signal morphology, highly varying with time and the physical states of the subject. In this paper, we present a novel PPG-based biometric authentication system based on convolutional neural networks. Contrary to previous approaches, our method extracts the PPG signal's biometric characteristics from its diffusive dynamics, characterized by geometric patterns image in the (p, q)-planes specific to the 0-1 test. The diffusive dynamics of the PPG signal are strongly dependent on the vascular bed's biostructure, which is unique to each individual, and highly stable over time and other psychosomatic conditions. Besides its robustness, our biometric method is anti-spoofing, given the convoluted nature of the blood network. Our biometric authentication system reaches very low Equal Error Rates (ERRs) with a single attempt, making it possible, by the very nature of the envisaged solution, to implement it in miniature components easily integrated into wearable biometric systems.Comment: 18 pages, 6 figures, 4 table