Problem Of User Authentication Research Articles

Deep features fusion for user authentication based on human activity

AbstractThe exponential growth in the use of smartphones means that users must constantly be concerned about the security and privacy of mobile data because the loss of a mobile device could compromise personal information. To address this issue, continuous authentication systems have been proposed, in which users are monitored transparently after initial access to the smartphone. In this study, the authors address the problem of user authentication by considering human activities as behavioural biometric information. The authors convert the behavioural biometric data (considered as time series) into a 2D colour image. This transformation process keeps all the characteristics of the behavioural signal. Time series does not receive any filtering operation with this transformation, and the method is reversible. This signal‐to‐image transformation allows us to use the 2D convolutional networks to build efficient deep feature vectors. This allows them to compare these feature vectors to the reference template vectors to compute the performance metric. The authors evaluate the performance of the authentication system in terms of Equal Error Rate on a benchmark University of Californy, Irvine Human Activity Recognition dataset, and they show the efficiency of the approach.

Authentication and Authorization of Users and Services in Dynamic Military SOA Environments

The problem of user authentication and authorization is usually being solved in a single system. Federated environment assumes heterogeneity of systems, which brings the problem of mutual users and services authentication and authorization. In this article the authors presented security requirements for cross domain information exchange in federated environments and a method of secure access to information resources on the basis of web services. Special attentionwas paid to authentication and authorization of users and services. As opportunities, there were presented solutions verified in multinational experimentations and exercises.

Binary PSO Variants for Feature Selection in Handwritten Signature Authentication

In this paper we propose modifications of the well-known algorithm of particle swarm optimization (PSO). These changes affect the mapping of the motion of particles from continuous space to binary space for searching in it, which is widely used to solve the problem of feature selection. The modified binary PSO variations were tested on the dataset SVC2004 dedicated to the problem of user authentication based on dynamic features of a handwritten signature. In the example of k-nearest neighbours (kNN), experiments were carried out to find the optimal subset of features. The search for the subset was considered as a multicriteria optimization problem, taking into account the accuracy of the model and the number of features.

USE OF MODERN INFORMATION TECHNOLOGIES IN THE DISTANCE LEARNING

Currently, the number of applicants who prefer distance education is growing every year. This form of learning reflects all the inherent components of the learning process such as goals, content, methods, organizational forms and means of learning. The widespread demands for this form of education and the modern realities caused by the COVID-19 pandemic have created the need the development and implementation of distance learning technologies.
 Ensuring educational dialogue in distance learning is done with the help of telecommunication technologies. The main technologies most widely used in this form of education include a variety of video lectures, electronic multimedia textbooks, computer training and testing systems, and other.
 In this article the new information technologies used in the process of distance learning discussed in detail. Although we discussed advantages and disadvantages of the new information technologies. In addition, distance learning using Internet technologies is gaining more and more popularity. The Internet has a number of specific features (openness, accessibility, variability, interactivity) that must be considered when designing, creating and conducting distance learning courses.
 The main strengths of this form of learning, in our opinion, are flexibility, modularity, accessibility, cost-effectiveness, mobility and manufacturability.
 Weaknesses include the lack of direct face-to-face communication, the mandatory availability of a personal computer and access to Internet resources, the problem of user authentication when testing knowledge, the high complexity of developing distance learning courses and others.
 Also considered are the main models the organization of distance learning, which are used in the leading universities in the world. These include: consortium, franchising, validation, distance audiences, projects, and open learning.
 Thus, despite the weaknesses, modern computer telecommunications is able to provide knowledge transfer and access to various educational information equally, and sometimes much more effectively than traditional teaching aids. A variety of educational technologies can not only ensure the active involvement of students in the learning process, but also allow you to manage this process, unlike most traditional learning environments.

Human posture tracking with flexible sensors for motion recognition

AbstractThe integration of conventional clothes with flexible electronics is a promising solution as a future‐generation computing platform. However, the problem of user authentication on this novel platform is still underexplored. This work uses flexible sensors to track human posture and achieves the goal of user authentication. We capture human movement pattern by four stretch sensors around the shoulder and one on the elbow. We introduce the long short‐term memory fully convolutional network (LSTM‐FCN), which directly takes noisy and sparse sensor data as input and verifies its consistency with the user's predefined movement patterns. The method can identify a user by matching movement patterns even if there are large intrapersonal variations. The authentication accuracy of LSTM‐FCN reaches 98.0%, which is 10.7% and 6.5% higher than that of dynamic time warping and dynamic time warping dependent.

Multilevel Authentication for Social Network

Nowadays, social network plays a vital role in communication. Normally user used social networks in daily activities. However, this left all online users susceptible to misuse and abuse. Recently, there has been a remarkable growth in number of hacking as well. Once the computer is online, anyone can have access to the network. Therefore, we proposed a secure social network site called SocialBook where users can post status, photos and connect with friends. This system is developed using PHP programming language and Iterative and Incremental Development methodology. The purpose of developing this system is to solve unsecured login accounts and lack of user authentication problem. This system applies the secret question procedure when the user wants to change their account password. Moreover, SocialBook use idle session timeout mechanism for additional security. When the user is idle for ten minutes, they will be logged out automatically. So, the user will be less worry about their account from being hacked and the identity impersonation by unauthorized user.

Multilevel Authentication for Social Network

Nowadays, social network plays a vital role in communication. Normally user used social networks in daily activities. However, this left all online users susceptible to misuse and abuse. Recently, there has been a remarkable growth in number of hacking as well. Once the computer is online, anyone can have access to the network. Therefore, we proposed a secure social network site called SocialBook where users can post status, photos and connect with friends. This system is developed using PHP programming language and Iterative and Incremental Development methodology. The purpose of developing this system is to solve unsecured login accounts and lack of user authentication problem. This system applies the secret question procedure when the user wants to change their account password. Moreover, SocialBook use idle session timeout mechanism for additional security. When the user is idle for ten minutes, they will be logged out automatically. So, the user will be less worry about their account from being hacked and the identity impersonation by unauthorized user.

An Accurate and Efficient User Authentication Mechanism on Smart Glasses Based on Iris Recognition

In modern society, mobile devices (such as smart phones and wearable devices) have become indispensable to almost everyone, and people store personal data in devices. Therefore, how to implement user authentication mechanism for private data protection on mobile devices is a very important issue. In this paper, an intelligent iris recognition mechanism is designed to solve the problem of user authentication in wearable smart glasses. Our contributions include hardware and software. On the hardware side, we design a set of internal infrared camera modules, including well-designed infrared light source and lens module, which is able to take clear iris images within 2~5 cm. On the software side, we propose an innovative iris segmentation algorithm which is both efficient and accurate to be used on smart glasses device. Another improvement to the traditional iris recognition is that we propose an intelligent Hamming distance (HD) threshold adaptation method which dynamically fine-tunes the HD threshold used for verification according to empirical data collected. Our final system can perform iris recognition with 66 frames per second on a smart glasses platform with 100% accuracy. As far as we know, this system is the world’s first application of iris recognition on smart glasses.

Using Preferences as User Identification in the Online Examination

User authentication is a very important online environment issue. More researches are needed to focus on enhancing user authentication methods for online examination. This paper is a review of online authentication methods for online examination and propose a novel authentication method called “Preferences Based Authentication” PrBA. The proposed method based on the exam taker design preferences chosen for online exams. A lot of design features could be applied to the exam interface, such as font (size, face, and style, colour), background colour, the number of questions per page, group question by (Type, difficulty) and timer type. These preferences have a close relationship with user characteristics, whether physical (vision, hearing, etc.), cognitive (memory, etc.), psychomotor (attention, focus, etc.), demographics (age, gender, etc.) or experiences (professional skills). The PrBA proposed in this paper could be used as an alternative to resolve the problem of user authentication within online exams.

Secure and Energy Efficient Model with Modified Offloading Algorithm in Mobile Cloud Computing

Mobile cloud computing is an evolving technology that is still unclear to many security problems and ensuring the security of data storage in cloud servers is one of the most challenging task. This paper proposes an algorithm which ensure to solve data protection and user authentication problems. In the proposed model an encryption and key exchanging mechanism has been described based on hybrid Dieffie-Hellman algorithm. Moreover, this paper focus on to resolve the waste energy in the network and for this purpose an offloading algorithm with dynamic energy aware model is proposed here. As a result it is analyzed that the higher the repetition rate of tasks the more energy is saved by Dynamic Energy Aware (DES) than Cloud Offload.

A survey of attacks on iris biometric systems

Biometric recognition has several applications that provide reliable solutions to the user authentication problem. Its widespread use and popularity is itself making it prone to several vulnerabilities. Iris is emerging as one of the most popular and accurate biometrics. Due to its inherent advantages and uniqueness, it is gaining popularity as a powerful authentication tool. However, the iris recognition systems may suffer from various attacks at different points during the authentication process. This article intends to review the popular attacks on the iris biometric, which affects its security, and present a survey on the approaches taken by various researchers to mitigate these attacks. The attacks have been divided into three categories, namely - user level, user-system interface level and stored database attacks. We present an overview of these attacks and analyse the algorithms proposed in the literature that are usually used to secure iris biometric systems from these attacks.

An Authentication and Authorization Solution for a Multiplatform Cloud Environment

ABSTRACTProviding security at all levels within the multiplatform cloud-computing environment is has not been properly solved due to a variety of problems arising from technical and human-based sources. This paper presents an authentication-and-authorization solution based on the Single Sign-On (SSO) approach for cloud-service users and administrators in a multiplatform environment. The system developed enables user authentication for clouds provided as Infrastructure as a Service system built up from different OS systems. The solution enables the use of different services based on credentials that are authenticated only once and enable simple and efficient administration of the relevant data. The paper briefly presents the problem of user authentication in cloud services from the security aspect and defines the user and system administrator requirements for a secure and efficient authentication system. The implemented solution for two different platforms and the associated OS, one proprietary (WMware) and one open-source (OpenStack), is briefly described.

Machine Learning Methods in Authentication Problems Using Password Keystroke Dynamics

We examine the problem of user authentication from keystroke dynamics. A new static authentication method that collects information about user keystrokes is described. Its applicability to the authentication problem is substantiated by experiments and the optimal conditions for the implementation of the method are chosen.

Improved perception-based spiking neuron learning rule for real-time user authentication

Spiking neural networks (SNNs) have been highly successful in spatiotemporal pattern recognition. As one of the most efficient supervised learning algorithms in spike sequences learning, the perceptron-based spiking neuron learning rule (PBSNLR) still has a relatively high computational complexity, which is difficult to use in a real-time system. In this paper, a novel method is presented to improve PBSNLR׳s efficiency without reducing its accuracy, and this method is applied to solve user authentication problem in real time. In our method, a user׳s behavioral biometric of sliding dynamic and finger pressure are selected as spatiotemporal features to recognize the user׳s identity. The temporal feature is obtained by the time coding of SNNs and the spatial feature is represented by the neurons׳ relative positions. Comprehensive experimental results demonstrate that our improved algorithm outperforms the traditional PBSNLR in terms of efficiency and exhibits excellent performance when identifying users of touch screen devices.

A new biometrics-based authentication protocol for smart card applications

In this paper, a complete protocol is proposed to address the problem of user authentication in applications involving smart cards. The protocol employs Schnorr identification protocol to prove the matching of the private key on the smart card to the associated public key of the user. The proposed protocol does not involve the private key stored on card directly but rather the associated public key. To enhance the security of the proposed protocol, the private key stored on card is extracted from the iris of the user to whom the card is being issued.

Biometric Template Security

Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.