Enhancing User Authentication Research Articles

Deep Learning-Based Biometric Finger Vein Authentication System for Enhanced Security

Biometrics, which uses human physiological characteristics, is a method for protecting personal information. Recently, finger vein authentication has become one of the most popular biometric techniques. This method offers high security and accuracy, making it a reliable form of biometric authentication. The system compares a person's vascular structure in their finger to previously collected data. Finger vein authentication works by identifying vein patterns beneath the skin's surface. The proposed system aims to enhance user authentication security by leveraging the uniqueness of finger vein patterns. The finger vein image is obtained from a database, and preprocessing is done using a Gaussian median filter in both spatial and frequency domains to remove noise. Image segmentation is performed through a line tracking method, which enhances image contrast. For feature extraction, the system utilizes Convolutional Neural Networks (CNN), and these features are matched with the stored finger vein database. A deep learning approach is then applied to classify users as genuine or imposters. In real-time, a scanner captures the finger vein image, which is sent to an Arduino board for storage and subsequently processed in MATLAB for classification. The result is transmitted through a GSM module as an alert or message, and the information is also stored in an IoT system for future reference. A GSM module is integrated with the user for communication. The proposed system achieves an accuracy of 96%, making it highly beneficial for security applications like access control, identity verification, banking, and financial transactions.

A Novel Deep Ensemble Learning to Enhance User Authentication in Autonomous Vehicles

A Novel Deep Ensemble Learning to Enhance User Authentication in Autonomous Vehicles

Gait-based identification using wearable multimodal sensing and attention neural networks

Advances in sensor technology have sparked a wave of innovation and progress in the domain of wearable devices. However, ensuring the security of these devices remains a critical concern for their users. This study proposes a novel identification framework that employs custom multimodal sensing insoles and deep learning techniques to contribute to the data security of wearable devices in a user-transparent manner. The insole incorporates an inertial sensing unit and ten force sensors to capture kinematic and kinetic information. For this implementation, we propose a lightweight multiclass classification deep model based on depthwise separable convolution and an enhanced attention mechanism, which operates over multiple signal channels. In designing the recognition model, we focused on two pivotal factors: (1) achieving an optimal balance between computational complexity and recognition accuracy, which is essential for models that operate on devices with limited computational power, and (2) introducing an enhanced attention mechanism that ensures high recognition accuracy without the stringent requirement for precise temporal alignment between sensor channels, which can be technically challenging to attain. We conducted extensive experiments to validate the proposed approach, utilizing a walking dataset collected from 82 young subjects. The results indicate that when using data from the multimodal sensing insole, a high recognition accuracy of 97.96 % for person identification is achieved, with a notably low model parameter count of 22,462. The results support the feasibility and effectiveness of sensing footwear-based gait identification. The proposed approach holds significant potential for enhancing user authentication methods across a broad range of scenarios while ensuring transparency and user-friendliness.

AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

This comprehensive study explores the integration and effectiveness of Artificial Intelligence (AI) in Identity and Access Management (IAM) within cloud environments. It primarily focuses on how AI can enhance user authentication, authorization, and access control, addressing the challenges and possibilities in cloud computing. The study adopts a mixed-methods approach, employing both quantitative and qualitative analyses. A survey involving 582 cybersecurity experts provides insights into the current state and potential of AI in IAM, while multiple regression analysis examines the impact of various factors on system effectiveness. Four hypotheses are explored: the impact of hardware and software configurations on system accuracy (H1), the influence of computational environments on reliability (H2), the role of demographic factors in user acceptance (H3), and the effect of technological enhancements on system performance and acceptance (H4). Findings indicate significant correlations between these factors and the effectiveness of AI in IAM. Notably, hardware configurations and security concerns influence system accuracy; computational environment variations affect system reliability; demographic factors impact user acceptance; and enhancements such as user feedback, advancements in AI technology, continuous learning algorithms, and system transparency improve performance and acceptance. These insights underscore the need for advanced hardware, standardized software, user-centric design, and continuous improvement in AI technologies for effective IAM in cloud environments. The study provides actionable recommendations for cloud service providers and developers, emphasizing the importance of involving users in development processes, ensuring transparency, and adopting adaptive algorithms. Future research directions include longitudinal studies on the impact of technological advancements and exploring demographic-specific responses to AI-integrated IAM solutions.

Enhancing User Authentication: An Approach Utilizing Context-Based Fingerprinting with Random Forest Algorithm

Enhancing User Authentication: An Approach Utilizing Context-Based Fingerprinting with Random Forest Algorithm

Enhancing User Authentication with Facial Recognition and Feature-Based Credentials

This research proposes a novel and trustworthy user authentication method that creates individualized and trusted credentials based on distinctive facial traits using facial recognition technology. The ability to easily validate user identification across various login methods is provided by this feature. The fundamental elements of this system are face recognition, feature extraction, and the hashing of characteristics to produce usernames and passwords. This method makes use of the OpenCV library, which is free software for computer vision. Additionally, it employs Hashlib for secure hashing and Image-based Deep Learning for Identification (IDLI) technology to extract facial tags. For increased security and dependability, the system mandates a maximum of ten characters for users and passwords. By imposing this restriction, the system increases its resilience by reducing any possible weaknesses in its defense. The policy also generates certificates that are neatly arranged in an Excel file for easy access and management. To improve user data and provide reliable biometric authentication, this study intends to create and implement a recognition system that incorporates cutting-edge approaches such as face feature extraction, feature hashing, and password creation. Additionally, the system has robust security features using face recognition.

An ECDSA Approach to Access Control in Knowledge Management Systems Using Blockchain

Access control has become problematic in several organizations because of the difficulty in establishing security and preventing malicious users from mimicking roles. Moreover, there is no flexibility among users in the participation in their roles, and even controlling them. Several role-based access control (RBAC) mechanisms have been proposed to alleviate these problems, but the security has not been fully realized. In this work, however, we present an RBAC model based on blockchain technology to enhance user authentication before knowledge is accessed and utilized in a knowledge management system (KMS). Our blockchain-based system model and the smart contract ensure that transparency and knowledge resource immutability are achieved. We also present smart contract algorithms and discussions about the model. As an essential part of RBAC model applied to KMS environment, trust is ensured in the network. Evaluation results show that our system is efficient.

Multimedia image data processing on smartphone for authentication

The spread of smartphones is rapidly increasing. Such smartphones mainly handle image and video data. In particular, there are many security problems that may occur at this time when there are many accesses to multimedia image data. But most systems use various technologies for user authentication such as identification/password (ID/PW), the certificate, One-Time Password (OTP), fingerprint/iris recognition, etc. When using ID/PW technology, the system is vulnerable, if ID/PW is disclosed to a hacker. The certificate or fingerprint/iris recognition technologies are more secure than ID/PW technology, but they require more cost, and they are complex to build. In this paper, we propose the method for enhancing user authentication. The proposed method improves security at a low cost using the user’s authentication information and the user’s smartphone IMEI information. In particular, IMEI information can be seen to provide a fast right and secure authentication mechanism to perform user authentication of multimedia image processing. In our research method, it is much safer and superior responsiveness than authentication methods using only user ID / Password on smartphones.

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.

User-centered Security for Protecting Patient Privacy for E-health Cloud Computing

E-health is the present communication structure in medicine especially in developed countries. Toward enhancing the quality of care and reduce the health care delivery cost, cloud Computing technology has been adopted. In recent times services such as exchange and share medical data among staff and then to the patients are one the main reasons behind using this technology in e-health. Hence, using cloud computing in e-health has many challenges particularly when dealing with electronic healthcare records (EHR).
 Cloud computing is an agglomeration of technologies, operating systems, storage, networking, virtualisation, each fraught with inherent security issues. For example, browser-based attacks, denial of service attacks and network intrusion become carry-over risks into cloud computing. It differs from traditional computing paradigms as it is scalable which can be encapsulated as an abstract entity to provide different levels of services to the clients.
 In this paper, we identified the users of e-health such as doctors, nurses and family members and then their security requirements are identified. An application with five stages toward encryption and decryption process is designed. Since trust is a critical factor in cloud computing, this project will investigate the obstacles that cause this technology lose its credibility in certain clouds. To enhance user authentication process, two-tier mechanisms are used to identify the user’s identity. While in confidentiality, it should be assured that information is shared only among authorised people or vendors by applying powerful cryptographic concepts. In this prototype application, the user will be able to protect his/her data and is responsible for providing a high level of security as long as these data are highly private and important.

An Efficient Framework for Enhancing User Authentication in Cloud Storage Using Digital Watermark

Security issues in cloud computing is one of the major reasons in slowing down its adoption by businesses and among these issues: weak user authentication. In fact, the use of text password is still relatively widespread, especially, for authentication in a cloud environment. Therefore, numerous approaches have been proposed to overcome this problem such as graphical passwords, biometric scans and 3D password objects. In this paper, we propose a cloud-based two-factor authentication framework called Two Levels Authentication Cloud (2LAC). The framework uses an image and a secret watermark as factors of authentication. Experimental results illustrate that 2LAC offers an efficient mechanism for enhancing user authentication in the cloud environment and can eliminate common types of attacks.

Secure User Authentication by using Biometric and Keystroke in Cloud

In last few years the data usage from internet has been increased at very high rate. The adaption of cloud in business organizations increased exponentially. But unfortunately the attacks on that data and transactions are also increasing. As the every authorized user has their own username and password to access their personal accounts, but as these details can be misused by an authorized user so there is a requirement of additional authentication step. The combination of keystroke biometric, voice authentication and cryptography is more efficient to authenticate the user and provide more security. Keystroke biometrics is based on the assumption the typing pattern of each user is unique and cryptography in use to secure the password. By using voice authentication password will reset. In this paper, looking forward at several processes for keystroke biometrics to enhance user authentication. The objective is to collect a keystroke-dynamics dataset, to develop a repeatable evaluation procedure, and to measure the performance of a range of detectors so that the results can be compared more accurately. The database is used to degree of variance of the user and to detect the authorization of the user.

Enhancing User Authentication and Encrypting Lob Data in OLE DB Provider for Database

Database is widely used in computer systems currently, and OLE DB is the main method for applications to access database on Microsoft's system. In order to store sensitive data in commercial database management system, application often encrypt the data before keeping it into database. UDF (User Defined Function) is helpful for applications in encrypting procedure, but it can't handle Lob (Long object) data. A secure OLE DB provider for enhancing user authentication and encrypting Lob data in database is proposed. By adding necessary attributes of user authentication and cipher algorithm to encrypt Lob data in OLE DB provider, the security of data stored in database is improved. Experiments show that the proposed OLE DB provider is transparent, efficient, easy to implement and reliable.

Schema of Enhancing User Authentication and Encrypting Lob Data in ODBC Driver for Database

For commercial database management system is not suitable for storing sensitive data, the data is often encrypted in application before keeping into database. Using UDF (User Defined Function) can simplify the encrypting procedure, but it can't handle Lob (Long object) data. A schema of enhancing user authentication and encrypting Lob data in ODBC (Open Database Connection) driver for database is prosed. By adding necessary attributes of user authentication and cipher algorithm to encrypt Lob data in ODBC driver, the security of data stored in database is improved. Experiments show that the schema is transparent, efficient, easy to implement and reliable.

An Efficient Novel Key Management Scheme for Enhancing User Authentication in A WSN

The Wireless Sensor Networks are energy constrained and are normally low cost and low power devices. These nodes are deployed over a specific area for specific goals. Due to energy and memory constraints, secure communication among these sensors is challenging management issue. In order to ensure security, proper connectivity among nodes and resilience against node capture, we propose a scheme called as Random Pre-Key distribution scheme which takes advantage of the binomial key pattern while creating and distributing keys. The value of keys would develop the number of patterns, which is given by the binomial distribution, which would be helpful in maintaining a key pool which is all though random in nature and following a pattern leads to more probability of network connection links. This paper provides a secured communication in WSNs environment and pairing user authentication has been proposed. We employ the idea of dividing the sensor network field into scattered nodes. Inside the scenario, one of the sensor nodes is selected as a server sensor node which is responsible for delivering the key. The novelty of the proposed scenario lies behind the idea of incorporating the sensor nodes along with the proper user authentications. We calculate the throughput involving a periodic traffic and obtained results from the xgraph utility with the use of Network Simulator. The results of this key scheme are obtained and show that improvement in terms of connectivity.

얼굴 정보 기반 일회용 패스워드 생성 메커니즘을 이용한 사용자 인증 시스템 설계 및 구현

최근 스마트폰을 이용한 인터넷뱅킹, 전자금융 서비스 및 인터넷전화 서비스 등을 이용할 수 있다. 스마트폰을 이용할 경우 보다 강화된 사용자 인증 기능이 제공되어야 한다. 본 연구에서는 스마트폰을 이용하여 각 사용자 얼굴 정보와 같은 바이오메트릭 ID 정보를 이용하여 일회용 패스워드를 생성하는 메커니즘을 구현하였다. 스마트폰내 카메라 모듈을 이용하여 얼굴 이미지를 캡춰하여 서버로 전송하면 서버에서는 일회용 바이오메트릭 ID를 생성하도록 하였다. 그리고 이를 기반으로 클라이언트에서 일회용 패스워드를 생성하는 시스템을 개발하였다. 본 연구에서 제시한 기법을 이용할 경우 스마트폰 기반 SIP 서비스에서의 사용자 인증을 보다 강화할 수 있다. Internet banking, electronic financial services and internet telephony service can be available on smart phone recently. In this case, more robust authentication mechanisms should be provided for enhancing security on it. In this study, a facial biometric ID based one-time password generation mechanism is designed and implemented for enhancing user authentication on smart phone. After capturing a facial biometric data using camera module on smart phone, it is sent to server to generate one-time biometric ID. Finally one-time password will be generated by client module after receiving the one time biometric ID based challenge token from the server. Using proposed biometric ID based one-time password mechanism, it is possible for us to provide more secure user authentication service on smart phone for SIP protocol.

스마트폰에서 음성 정보를 이용한 일회용 패스워드(V-OTP) 기반 사용자 인증 메커니즘 설계 및 구현

음성 정보를 이용한 인증과정을 통해 스마트폰 서비스에서의 보안성을 향상시킬 필요가 있다. 본 연구에서는 스마트폰 사용자의 음성 정보를 이용하여 일회용 패스워드를 생성하는 메커니즘을 설계 및 구현하였다. 서버에서 전송된 PIN 값에 대해 스마트폰내 마이크 장치를 이용하여 음성 데이터를 캡춰하여 서버로 전송하면 서버에서는 검증 과정을 수행하고 일회용 토큰을 생성하도록 하였다. 그리고 클라이언트-서버간 상호 인증 과정 수행 후에 최종적으로 스마트폰 환경에서 음성 정보를 이용하여 일회용 패스워드(V-OTP)를 생성하는 메커니즘을 개발하였다. 본 연구에서 제시한 기법을 이용할 경우 스마트폰 기반 서비스에서의 사용자 인증을 보다 강화할 수 있다. It is necessary for us to enhance the security service on smart phone by using voice data on authentication procedure. In this study, a voice data based one-time password generation mechanism is designed and implemented for enhancing user authentication on smart phone. After receiving a PIN value from the server, a user inputs his/her own voice biometric data using mike device on smart phone. And then this captured a voice biometric data will be used to generate one-time token on server side after verification procedures. Based on those mutual authentication steps, a voice data based one-time password(V-OTP) will be generated by client module after receiving the one-time token from the server finally. Using proposed voice one-time password mechanism, it is possible for us to provide more secure user authentication service on smart phone.

Beyond the PIN: Enhancing user authentication for mobile devices

There is now an increasing need for an enhanced level of user authentication on mobile devices. In this article, Steven Furnell, Nathan Clarke and Sevasti Karazouni begin by examining the existing provision, which is dominated by PIN and password-based approaches. They established that these may be both inconvenient and inadequate for securing modern devices and services. Mobile devices have changed significantly over the last decade, in terms of both their form factor and underlying capabilities. The introduction of third generation (3G) technologies has provided the underlying mechanism for a wide variety of innovative data-orientated services, with approximately one million users every day adopting these new features. 1

Toward a Biometric Security Layer in Accounting Systems

This paper discusses theoretical and practical issues related to the use of a biometric-enabled security layer in accounting systems aimed at enhancing user authentication and reducing control risk. Originating in criminology, biometric technology has matured over the years with applications in diverse disciplines. However, its use in business and accounting is still in its infancy, and many issues about its role in information systems security are unresolved. The paper proposes an access decision framework that draws from the strategy and risk assessment literature to model processes where biometrics might be used to reduce control risk. Despite its potential strengths, biometric technology is not a panacea and represents one element in a portfolio of security mechanisms needed to protect information resources. The paper discusses challenges in implementing biometric technology and identifies avenues for future research.