scholarly journals Biometrics in cyber defense

2020 ◽  
Vol 309 ◽  
pp. 02003
Author(s):  
Gabriela Mogos
Keyword(s):  
Literature Review ◽  
Iris Recognition ◽  
User Authentication ◽  
Smart Devices ◽  
Biometric Identification ◽  
Cyber Defense ◽  
Security Risks ◽  
Strong Case ◽  
Current Practices

Biometric identification is an up and coming authentication method. The growing complexity of and overlap between smart devices, usability patterns and security risks make a strong case for securer and safer user authentication. This paper aims to offer a broad literature review on iris recognition and biometric cryptography to better understand current practices, propose possible future enhancements and anticipate possible future usability and security developments.

scholarly journals IRIS TECHNOLOGY: A REVIEW ON IRIS BASED BIOMETRIC SYSTEMS FOR UNIQUE HUMAN IDENTIFICATION

2018 ◽  
Vol 6 (1) ◽  
pp. 80-90
Author(s):  
M V Bramhananda Reddy ◽  
V Goutham
Keyword(s):  
Iris Recognition ◽  
Human Identification ◽  
Smart Devices ◽  
Biometric Identification ◽  
Great Precision ◽  
Iris Localization ◽  
Biometric Systems ◽  
Real Time Applications ◽  
Multimodal Biometric Systems ◽  
Biometric Features

Biometric features are widely used in real time applications for unique human identification. Iris is one of the physiological biometric features which are regarded as highly reliable in biometric identification systems. Often iris is combined with other biometric features for robust biometric systems. It is also observed that biometrics is combined with cryptography for stronger security mechanisms. Since iris is unique for all individuals across the globe, many researchers focused on using iris or along with other biometrics for security with great precision. Multimodal biometric systems came into existence for better accuracy in human authentication. However, iris is considered to be most discriminatory of facial biometrics. Study of iris based human identification in ideal and non-cooperative environments can provide great insights which can help researchers and organizations that depend on iris-based biometric systems. The technical knowhow of iris strengths and weaknesses can be great advantage. This is more important in the wake of widespread use of smart devices which are vulnerable to attacks. This paper throws light into various iris-based biometric systems, issues with iris in the context of texture comparison, cancellable biometrics, iris in multi-model biometric systems, iris localization issues, challenging scenarios pertaining to accurate iris recognition and so on.

scholarly journals A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4212
Author(s):  
Priscila Morais Argôlo Bonfim Estrela ◽  
Robson de Oliveira Albuquerque ◽  
Dino Macedo Amaral ◽  
William Ferreira Giozza ◽  
Rafael Timóteo de Sousa Júnior
Keyword(s):  
User Authentication ◽  
Internet Banking ◽  
Supervised Machine Learning ◽  
Smart Devices ◽  
Static Verification ◽  
User Behaviors ◽  
Legitimate User ◽  
Continuous User ◽  
Mobile Banking Applications ◽  
Effective Layer

As smart devices have become commonly used to access internet banking applications, these devices constitute appealing targets for fraudsters. Impersonation attacks are an essential concern for internet banking providers. Therefore, user authentication countermeasures based on biometrics, whether physiological or behavioral, have been developed, including those based on touch dynamics biometrics. These measures take into account the unique behavior of a person when interacting with touchscreen devices, thus hindering identitification fraud because it is hard to impersonate natural user behaviors. Behavioral biometric measures also balance security and usability because they are important for human interfaces, thus requiring a measurement process that may be transparent to the user. This paper proposes an improvement to Biotouch, a supervised Machine Learning-based framework for continuous user authentication. The contributions of the proposal comprise the utilization of multiple scopes to create more resilient reasoning models and their respective datasets for the improved Biotouch framework. Another contribution highlighted is the testing of these models to evaluate the imposter False Acceptance Error (FAR). This proposal also improves the flow of data and computation within the improved framework. An evaluation of the multiple scope model proposed provides results between 90.68% and 97.05% for the harmonic mean between recall and precision (F1 Score). The percentages of unduly authenticated imposters and errors of legitimate user rejection (Equal Error Rate (EER)) are between 9.85% and 1.88% for static verification, login, user dynamics, and post-login. These results indicate the feasibility of the continuous multiple-scope authentication framework proposed as an effective layer of security for banking applications, eventually operating jointly with conventional measures such as password-based authentication.

scholarly journals Scoot over Smart Devices: The Invisible Costs of Rental Scooters

2019 ◽  
Vol 17 (1/2) ◽  
pp. 191-197 ◽  
Author(s):  
Andrew Boyles Petersen
Keyword(s):  
North America ◽  
Data Security ◽  
Mobile Apps ◽  
Smart Devices ◽  
Gps Data ◽  
Security Risks ◽  
The Past ◽  
Last Mile ◽  
User Data ◽  
Consumer Data

In the past year, transportation rental companies, including Bird, Lime, and Spin, have dropped hundreds of thousands of rental scooters across North America. Relying on mobile apps and scooter-mounted GPS units, these devices have access to a wide-variety of consumer data, including location, phone number, phone metadata, and more. Pairing corroborated phone and scooter GPS data with a last-mile transportation business model, scooter companies are able to collect a unique, highly identifying dataset on users. Data collected by these companies can be utilized by internal researchers or sold to advertisers and data brokers. Access to so much consumer data, however, poses serious security risks. ­Although Bird, Lime, and Spin posit electric scooters as environmentally friendly and accessible transportation, they also allow for unethical uses of user data through vaguely-worded terms of service. To promote more equitable transportation practices, this article will explore the implications of dockless scooter geotracking, as well as related infrastructure, privacy, and data security ramifications.

NomadiKey: User authentication for smart devices based on nomadic keys

2017 ◽  
Vol 28 (1) ◽  
pp. e1998 ◽  
Author(s):  
Artur Souza ◽  
Ítalo Cunha ◽  
Leonardo B Oliveira
Keyword(s):  
User Authentication ◽  
Smart Devices

Keystroke Dynamics

2019 ◽  
pp. 183-207
Author(s):  
Senthil Kumar A. V. ◽  
Rathi M.
Keyword(s):  
Online Learning ◽  
Video Surveillance ◽  
Iris Recognition ◽  
User Authentication ◽  
Surveillance Systems ◽  
Keystroke Dynamics ◽  
Detailed Review ◽  
Online Tests ◽  
Biometric Based Authentication ◽  
The Way

Online learning has entirely transformed the way of learning by the students. Online tests and quizzes play an important role in online learning, which provides accurate results to the instructor. But, the learners use different methods to cheat during online exams such as opening a browser to search for the answer or a document in the local drive, etc. They are not authenticated once they login and progress to attend the online exams. Different techniques are used in authenticating the students taking up the online exams such as audio or video surveillance systems, fingerprint, or iris recognition, etc. Keystroke dynamics-based authentication (KDA) method, a behavioral biometric-based authentication model has gained focus in authenticating the users. This chapter proposes the usage of KDA as a solution to user authentication in online exams and presents a detailed review on the processes of KDA, the factors that affect the performance of KDA, their applications in different domains, and a few keystroke dynamics-based datasets to authenticate the users during online exams.

scholarly journals Smart Manufacturing Systems and Applied Industrial Technologies for a Sustainable Industry: A Systematic Literature Review

2020 ◽  
Vol 10 (8) ◽  
pp. 2897
Author(s):  
Raffaele Cioffi ◽  
Marta Travaglioni ◽  
Giuseppina Piscitelli ◽  
Antonella Petrillo ◽  
Adele Parmentola
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Circular Economy ◽  
Manufacturing Systems ◽  
Business Models ◽  
New Technologies ◽  
Smart Manufacturing ◽  
Smart Devices ◽  
Digital Innovation ◽  
Smart Manufacturing Systems

Smart manufacturing is considered as a new paradigm that makes work smarter and more connected, bringing speed and flexibility through the introduction of digital innovation. Today, digital innovation is closely linked to the “sustainability” of companies. Digital innovation and sustainability are two inseparable principles that are based on the concept of circular economy. Digital innovation enables a circular economy model, promoting the use of solutions like digital platforms, smart devices, and artificial intelligence that help to optimize resources. Thus, the purpose of the research is to present a systematic literature review on what enabling technologies can promote new circular business models. A total of 31 articles were included in the study. Our results showed that realization of the circular economy involved two main changes: (i) managerial changes and (ii) legislative changes. Furthermore, the creation of the circular economy can certainly be facilitated by innovation, especially through the introduction of new technologies and through the introduction of digital innovations.

scholarly journals Data Improvement Model Based on ECG Biometric for User Authentication and Identification

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2920 ◽  
Author(s):  
Alex Barros ◽  
Paulo Resque ◽  
João Almeida ◽  
Renato Mota ◽  
Helder Oliveira ◽  
...  
Keyword(s):  
User Authentication ◽  
Personal Data ◽  
Large Data ◽  
Real Data ◽  
Rejection Rate ◽  
Security Requirements ◽  
Biometric Identification ◽  
Data Set ◽  
Rapid Spread ◽  
Data Improvement

The rapid spread of wearable technologies has motivated the collection of a variety of signals, such as pulse rate, electrocardiogram (ECG), electroencephalogram (EEG), and others. As those devices are used to do so many tasks and store a significant amount of personal data, the concern of how our data can be exposed starts to gain attention as the wearable devices can become an attack vector or a security breach. In this context, biometric also has expanded its use to meet new security requirements of authentication demanded by online applications, and it has been used in identification systems by a large number of people. Existing works on ECG for user authentication do not consider a population size close to a real application. Finding real data that has a big number of people ECG’s data is a challenge. This work investigates a set of steps that can improve the results when working with a higher number of target classes in a biometric identification scenario. These steps, such as increasing the number of examples, removing outliers, and including a few additional features, are proven to increase the performance in a large data set. We propose a data improvement model for ECG biometric identification (user identification based on electrocardiogram—DETECT), which improves the performance of the biometric system considering a greater number of subjects, which is closer to a security system in the real world. The DETECT model increases precision from 78% to 92% within 1500 subjects, and from 90% to 95% within 100 subjects. Moreover, good False Rejection Rate (i.e., 0.064003) and False Acceptance Rate (i.e., 0.000033) were demonstrated. We designed our proposed method over PhysioNet Computing in Cardiology 2018 database.

scholarly journals A Nonfiducial PPG-Based Subject Authentication Approach Using the Statistical Features of DWT-Based Filtered Signals

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Turky N. Alotaiby ◽  
Fatima Aljabarti ◽  
Gaseb Alotibi ◽  
Saleh A. Alshebeili
Keyword(s):  
Iris Recognition ◽  
Feature Vector ◽  
Identity Authentication ◽  
Smart Devices ◽  
Support Vector ◽  
Svm Classifier ◽  
Discrete Wavelet ◽  
Statistical Features ◽  
Authentication System ◽  
Signal Band

Nowadays, there is a global change in lifestyle that is moving more toward the use of e-services and smart devices which necessitate the verification of user identity. Different organizations have put into place a range of technologies, hardware, and/or software to authenticate users using fingerprints, iris recognition, and so forth. However, cost and reliability are significant limitations to the use of such technologies. This study presents a nonfiducial PPG-based subject authentication system. In particular, the photoplethysmogram (PPG) signal is first filtered into four signals using the discrete wavelet transform (DWT) and then segmented into frames. Ten simple statistical features are extracted from the frame of each signal band to compose the feature vector. Augmenting the feature vector with the same features extracted from the 1st derivative of the corresponding signal is investigated, along with different fusion approaches. A support vector machine (SVM) classifier is then employed for the purpose of identity authentication. The proposed authentication system achieved an average authentication accuracy of 99.3% using a 15 sec frame length with the augmented multiband approach.

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