scholarly journals Robustness of Rhythmic-Based Dynamic Hand Gesture with Surface Electromyography (sEMG) for Authentication

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2143
Author(s):  
Alex Ming Hui Wong ◽  
Masahiro Furukawa ◽  
Taro Maeda
Keyword(s):  
Face Recognition ◽  
Surface Electromyography ◽  
Acceptance Rate ◽  
The Other ◽  
Hand Gesture ◽  
Rhythmic Pattern ◽  
False Acceptance Rate ◽  
Trade Off ◽  
The Cost ◽  
False Acceptance

Authentication has three basic factors—knowledge, ownership, and inherence. Biometrics is considered as the inherence factor and is widely used for authentication due to its conveniences. Biometrics consists of static biometrics (physical characteristics) and dynamic biometrics (behavioral). There is a trade-off between robustness and security. Static biometrics, such as fingerprint and face recognition, are often reliable as they are known to be more robust, but once stolen, it is difficult to reset. On the other hand, dynamic biometrics are usually considered to be more secure due to the constant changes in behavior but at the cost of robustness. In this paper, we proposed a multi-factor authentication—rhythmic-based dynamic hand gesture, where the rhythmic pattern is the knowledge factor and the gesture behavior is the inherence factor, and we evaluate the robustness of the proposed method. Our proposal can be easily applied with other input methods because rhythmic pattern can be observed, such as during typing. It is also expected to improve the robustness of the gesture behavior as the rhythmic pattern acts as a symbolic cue for the gesture. The results shown that our method is able to authenticate a genuine user at the highest accuracy of 0.9301 ± 0.0280 and, also, when being mimicked by impostors, the false acceptance rate (FAR) is as low as 0.1038 ± 0.0179.

scholarly journals Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls

2020 ◽  
Vol 12 (7) ◽  
pp. 2767 ◽  
Author(s):  
Víctor Yepes ◽  
José V. Martí ◽  
José García
Keyword(s):  
Black Hole ◽  
Sustainable Design ◽  
Retaining Walls ◽  
The Other ◽  
Trade Off ◽  
Construction Company ◽  
Geometric Variables ◽  
The Stability ◽  
The Cost ◽  
Black Hole Algorithm

The optimization of the cost and CO 2 emissions in earth-retaining walls is of relevance, since these structures are often used in civil engineering. The optimization of costs is essential for the competitiveness of the construction company, and the optimization of emissions is relevant in the environmental impact of construction. To address the optimization, black hole metaheuristics were used, along with a discretization mechanism based on min–max normalization. The stability of the algorithm was evaluated with respect to the solutions obtained; the steel and concrete values obtained in both optimizations were analyzed. Additionally, the geometric variables of the structure were compared. Finally, the results obtained were compared with another algorithm that solved the problem. The results show that there is a trade-off between the use of steel and concrete. The solutions that minimize CO 2 emissions prefer the use of concrete instead of those that optimize the cost. On the other hand, when comparing the geometric variables, it is seen that most remain similar in both optimizations except for the distance between buttresses. When comparing with another algorithm, the results show a good performance in optimization using the black hole algorithm.

scholarly journals Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1568
Author(s):  
Junmo Kim ◽  
Geunbo Yang ◽  
Juhyeong Kim ◽  
Seungmin Lee ◽  
Ko Keun Kim ◽  
...  
Keyword(s):  
Incremental Learning ◽  
Physical State ◽  
Acceptance Rate ◽  
Support Vector ◽  
Ecg Signal ◽  
Biometric Authentication ◽  
False Acceptance Rate ◽  
Ecg Signals ◽  
Using Data ◽  
False Acceptance

Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We propose an adaptive ECG-based authentication method that performs incremental learning to identify ECG signals from a subject under a variety of measurement conditions. An incremental support vector machine (SVM) is adopted for authentication implementing incremental learning. We collected ECG signals from 11 subjects during 10 min over six days and used the data from days 1 to 5 for incremental learning, and those from day 6 for testing. The authentication results show that the proposed system consistently reduces the false acceptance rate from 6.49% to 4.39% and increases the true acceptance rate from 61.32% to 87.61% per single ECG wave after incremental learning using data from the five days. In addition, the authentication results tested using data obtained a day after the latest training show the false acceptance rate being within reliable range (3.5–5.33%) and improvement of the true acceptance rate (70.05–87.61%) over five days.

scholarly journals Keystroke Dynamic Authentication Using Combined MHR (Mean of Horner’s Rules) and Standard Deviation

2018 ◽  
pp. 13-18 ◽  
Author(s):  
Didih Rizki Chandranegara ◽  
Fauzi Dwi Setiawan Sumadi
Keyword(s):  
Standard Deviation ◽  
High Accuracy ◽  
Previous Method ◽  
Acceptance Rate ◽  
Biometric Authentication ◽  
False Acceptance Rate ◽  
False Acceptance ◽  
Keystroke Dynamic ◽  
Dynamic Authentication

Keystroke Dynamic Authentication used a behavior to authenticate the user and one of biometric authentication. The behavior used a typing speed a character on the keyboard and every user had a unique behavior in typing. To improve classification between user and attacker of Keystroke Dynamic Authentication in this research, we proposed a combination of MHR (Mean of Horner’s Rules) and standard deviation. The results of this research showed that our proposed method gave a high accuracy (93.872%) than the previous method (75.388% and 75.156%). This research gave an opportunity to implemented in real login system because our method gave the best results with False Acceptance Rate (FAR) is 0.113. The user can be used as a simple password and ignore a worrying about an account hacking in the system.

Collaborative Design Using Trade-Off Satisfying Method in Supervisor System

2000 ◽  
Author(s):  
Tomoyuki Miyashita ◽  
Hiroshi Yamakawa
Keyword(s):  
Data Envelopment Analysis ◽  
Decision Maker ◽  
Collaborative Design ◽  
Evaluation Criteria ◽  
The Other ◽  
Data Envelopment ◽  
Trade Off ◽  
Numerical Examples ◽  
Financial Difficulties ◽  
The Cost

Abstract Recent years, financial difficulties led engineers to look for not only the efficiency of the function of a product but also the cost of its development. In order to reduce the time for the development, engineers in each discipline have to develop and improve their objectives collaboratively. Sometimes, they have to cooperate with those who have no knowledge at all for their own disciplines. Collaborative designs have been studied to solve these kinds of the problems, but most of them need some sorts of negotiation among disciplines and assumes that these negotiations will be done successfully. However, in the most cases of real designs, manager of each discipline does not want to give up his or her own objectives to stress on the other objectives. In order to carry out these negotiations smoothly, we need some sort of evaluation criteria which will show efficiency of the product considering the designs by each division and if possible, considering the products of the competitive company, too. In this study, we use Data Envelopment Analysis (DEA) to calculate the efficiency of the design and showed every decision maker the directions of the development of the design. We will call here these kinds of systems as supervisor systems and implemented these systems in computer networks that every decision maker can use conveniently. Through simple numerical examples, we showed the effectiveness of the proposed method.

scholarly journals A STATIC SIGNATURE VERIFICATION SYSTEM BASED ON A COOPERATING NEURAL NETWORKS ARCHITECTURE

1994 ◽  
Vol 08 (03) ◽  
pp. 679-692 ◽  
Author(s):  
HUBERT CARDOT ◽  
MARINETTE REVENU ◽  
BERNARD VICTORRI ◽  
MARIE-JOSÈPHE REVILLET
Keyword(s):  
Neural Networks ◽  
Large Scale ◽  
Rejection Rate ◽  
Acceptance Rate ◽  
Signature Verification ◽  
Geometrical Parameters ◽  
False Acceptance Rate ◽  
Static Information ◽  
Handwritten Signature ◽  
False Acceptance

We are applying neural networks to the problem of handwritten signature verification. Our system is working on checks, so we can only use the static information (the image). This static information is used in three representations: geometrical parameters, outline and image. Our system is composed of several neural networks which cooperate together during the learning and decision phases. The performances in generalization, obtained with a large-scale database of 6000 signatures from real checks on random forgeries, are False Acceptance Rate (FAR)=2% and False Rejection Rate (FRR)=4%.

Distance Bounding Protocol with Adjustable False Acceptance Rate

2011 ◽  
Vol 15 (4) ◽  
pp. 434-436 ◽  
Author(s):  
Dae Hyun Yum ◽  
Jin Seok Kim ◽  
Sung Je Hong ◽  
Pil Joong Lee
Keyword(s):  
Acceptance Rate ◽  
False Acceptance Rate ◽  
Distance Bounding Protocol ◽  
False Acceptance

Authentication Based on Seating Pressure Distribution using the MT System

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
Shigeomi Koshimizu ◽  
Atsushi Koizumi
Keyword(s):  
Pressure Distribution ◽  
Rejection Rate ◽  
Acceptance Rate ◽  
New Method ◽  
Biometric Authentication ◽  
False Acceptance Rate ◽  
False Rejection Rate ◽  
Feature Values ◽  
False Acceptance ◽  
False Rejection

This paper proposes a system for authentication based on seating pressure distribution, using the MT system as a new method of biometric authentication that is difficult to forge and does not inconvenience users. The main characteristic is that the only action required of the user is to sit down. Feature values were extracted based on the pressure distribution when individuals seat, and individual users were distinguished from other persons by means of the Mahalanobis-Taguchi (MT) system used in quality engineering. The result of the experiment was a False Rejection Rate of 2.2% and a False Acceptance Rate of 1.1%. 

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