User Authentication Research Articles

An Expense Tracker

Abstract: The Expense Tracker project aims to provide a user-friendly platform for individuals or households to track their expenses efficiently. In today's fast-paced world, managing finances can be challenging, and this project seeks to simplify the process by offering a comprehensive solution. The project offers a range of features to help users manage their expenses effectively. It allows users to record their daily expenses, categorize them into different categories such as food, transportation, bills, and entertainment, and set budget limits for each category. The system provides notifications when users exceed their budget limits, helping them stay on track with their financial goals. One of the key features of the Expense Tracker project is its ability to analyze spending patterns over time. Users can view their expense history through interactive charts and graphs, allowing them to identify trends and make informed decisions about their finances. This feature is particularly useful for budget planning and identifying areas where expenses can be reduced. Security is a top priority for the Expense Tracker project. The system uses secure user authentication to ensure that only authorized users have access to their financial data. All data is encrypted to protect it from unauthorized access, providing users with peace of mind about the security of their information.

Implementation of Personal Cloud using Cryptography

Abstract: This Python-based personal cloud application leverages Flask and cryptography to establish a secure file storage system. Employing the Fernet encryption algorithm, the server encrypts uploaded files, ensuring data confidentiality. Users can securely upload, store, and download files, with each file automatically encrypted upon upload and decrypted for download. While this example prioritizes simplicity, a production-ready system should include robust user authentication, access controls, and further security enhancements. The abstract encapsulates the project's essence, highlighting its focus on file security within a personal cloud environment while acknowledging the need for additional features in a real-world deployment.

Portal for Various National and International Scholarship

Abstract: This abstract presents the development of a comprehensive portal for accessing various national and international scholarship opportunities. Built using Python Django framework, this portal aims to streamline the process of discovering scholarships, thereby facilitating access to education for a broader demographic. The portal aggregates scholarship listings from diverse sources, including government, educational institutions, and private organizations, offering a centralized platform for users to explore available opportunities. Through intuitive search and filtering functionalities, users can efficiently navigate through a vast array of scholarships tailored to their preferences, including academic background, field of study, and eligibility criteria. Key features of the portal include user authentication, personalized profiles, enhancing user engagement and facilitating tailored recommendations based on individual preferences and qualifications. Furthermore, the portal prioritizes user experience through responsive design, ensuring accessibility across various devices and platforms.

A Survey on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity. Keywords: Graphical Password Authenticator, User Authentication, Cybersecurity, Digital Security, Encryption Technologies, User-Centric Approach, Brute Force Resistance, Keyloggers Protection.

Tech Quest Language Learning

Tech Quest Language Learning is an innovative web based platform designed to facilitate language learning through interactive quizzes tailored for engineering students and professionals. The platform offers a diverse range of quizzes covering various engineering subjects, providing users with an engaging and effective way to test their knowledge and skills. Through a user-friendly interface, participants can navigate seamlessly between quizzes, receive instant feedback on their performance, and track their scores over time. Additionally, the platform incorporates user authentication mechanisms, ensuring secure access to personalized learning experiences. With its emphasis on interactivity, accessibility, and user engagement, "Tech Quest Language Learning" aims to enhance language proficiency and academic success in the engineering domain.

A Secure Biometric-Based User Authentication Scheme for Cyber-Physical Systems in Healthcare

A Secure Biometric-Based User Authentication Scheme for Cyber-Physical Systems in Healthcare

A Research on Graphical Password Strategy Authentication

In an ever-evolving digital realm, ensuring the security and reliability of software applications has become increasingly crucial. The continuous advancement of technology also brings about more complex cyber threats, emphasizing the urgent need to identify and address vulnerabilities. In response to this growing imperative, we introduce "Graphical Password Authenticator: A Novel Approach to Secure User Authentication." The Graphical Password Authenticator reimagines the conventional user authentication process by utilizing graphical elements and innovative techniques. It provides a secure and user-friendly alternative to traditional text-based passwords, offering enhanced protection against unauthorized access. By incorporating graphical images, patterns, or other visual cues, users can create unique and memorable authentication credentials that are difficult for malicious actors to compromise. This approach offers a more intuitive and engaging way for users to access their accounts while significantly reducing the risk of password-related security breaches. The Graphical Password Authenticator system ensures robust security through a combination of graphical recognition and encryption technologies. It is designed to be resistant to common attack methods such as brute force and keyloggers, providing a higher level of protection for user accounts and sensitive information. This novel approach to user authentication fosters a secure and user-centric environment, making it a promising solution for the ever-evolving digital landscape. The Graphical Password Authenticator is a groundbreaking step at the intersection of user authentication and innovation. By redefining the way users prove their identity through memorable graphical elements, this approach empowers users with a more secure and intuitive means of accessing their digital resources. This paradigm shift in authentication methods showcases the potential of technology to enhance user security and create a safer digital future, ultimately bridging the gap between user convenience and robust cybersecurity.

Enhancing privacy and security in 5G networks with an anonymous handover protocol based on Blockchain and Zero Knowledge Proof

The latest advancement in cellular technology, 5G, has the ability to facilitate various applications such as Device-to-Device (D2D) communication, vehicular communications, and the Internet of Everything (IoE). However, the technology is faced with challenges related to user privacy, resource management, handover authentication, and security of the air interface and internet channels. Moreover, the use of specialized base stations such as wireless Access Points (AP) and Road-Side Units (RSU) in vehicular communications may be owned by subscribers outside formal network operators. The conventional handover authentication schemes have a lengthy latency period that conflicts with the 5G quality of service. To tackle these challenges, this paper presents an anonymous scheme that utilizes Blockchain and Zero Knowledge Proof (ZKP) to ensure efficient privacy in the handover protocol of 5G Networks. The proposed scheme has been thoroughly evaluated for security and privacy and has shown to be resistant to identity catching, location area tracing, and replay attacks while achieving Forward/Backward secrecy. Furthermore, the performance evaluation of the proposed scheme indicates that it is efficient and speedy as it involves a limited number of messages, low computation, and does not necessitate the involvement of the Home Network (HN) in the authentication or handover protocols. A diligently crafted BAHO authentication protocol, following cryptographic principles, guarantees robust security against the Real-or-Random model. This results in a seamless and secure transition for User Equipment, upholding confidentiality, integrity, and authenticity during handovers between Access Points.

A BlockChain-Based IoT Data Securing and Sharing System for Attendance Management

Objective: An Internet of Things (IoT) network has constraints on power consumption, processing power and security of end devices in the network. On the other hand, blockchain technology has some difficulties in storage capacity, data privacy, the ability to revoke consent, energy usage, scalability, and speed. To overcome the individual limitations of these two technologies, we integrate these two to propose a new design with an intention to authenticate, secure and share data pertaining to attendance system. In this present work the primary implementation details of our proposed work regarding coding are analyzed and a straightforward solution is offered by using indexing. Methods: Through our proposed work we introduce a multifaceted authentication system for user device substantiation, a Public Key Infrastructure (PKI) and RSA (Rivest-Shamir-Adleman) based blockchain implementation for data sharing and a rule-based access control scheme used for accessing data. Findings: The system can work with unidirectional and bidirectional IoT networks, and the data is stored on blockchain, providing more security to the data generated on the IoT network. Blockchain technology is utilized to offer a solution for certain problems encountered within a widespread network. Furthermore, a multi-factor authentication scheme is introduced and a rule-based access control scheme to access the data. Novelty: The blockchain is emerging which can be used to decentralize management and protect sensitive data. In a blockchain based attendance system, no administrative authority is permitted to modify or erase data. The individual who adds a data entry to the blockchain cannot later deny their involvement in the action. On the blockchain, all of the data and history are accessible to every participant. The blockchain based attendance system needs to offer a database that can be trusted, secure, and impossible to manipulate. Keywords: Blockchain (BC), Internet of Things (IoT), Student Attendance Management (SAM), User Authentication Key (UAK), Data Sharing

A secure and efficient authentication key agreement scheme for industrial internet of things based on edge computing

Industrial Internet of Things (IIoT) is a pivotal driving force behind the intelligent transformation of the global industrial system, bringing about a gradual shift in production methods. However, due to users completing remote access and data transmission through open channels, ensuring user legitimacy and data security has become an important factor in IIoT. In addition, resource limited users or devices need to collect and publish corresponding messages while also timely processing instant messages obtained from the network. Leveraging edge computing technology effectively mitigates the transmission time of messages, addressing the challenges of high computing pressure and prolonged response time associated with cloud server computing. Therefore, investigating authentication key agreement based on edge computing in the IIoT environment holds substantial theoretical significance and practical importance. This article introduces an IIoT authentication that ensures both security and efficiency by integrating elliptic curve cryptography and three-factor authentication. Within this scheme, the user and the edge server accomplish security authentication. Through security analysis, the proposed scheme is proven to meet the essential security requirements. Performance analysis shows that it achieves higher security, supports more functions, and achieves lower computational and communication costs compared to related schemes.

Travel Itinerary: Travel lookout begins here

This research paper aims to develop a mobile application that serves as a straightforward travel guide, enhancing the exploration experience for travellers while simplifying decision-making by providing essential information without unnecessary complexities. The user-friendly design prioritises easy navigation and clear details, ensuring that users can effortlessly access the information they need. The integrated map feature allows users to find their routes effortlessly, while real-time weather updates for destinations help travellers plan accordingly and adapt to changing conditions. Going beyond basic navigation, the app offers valuable insights into popular attractions and cultural events, enriching the travel experience with curated information that highlights the best each destination has to offer. To streamline decision-making further, the app recommends top dining and accommodation options, removing the hassle and uncertainty from choosing where to eat and stay. These recommendations are based on user reviews and ratings, ensuring quality and reliability. In essence, this app is a user-centric tool designed to eliminate the stress associated with travel decisions, making it an invaluable companion for those seeking a straightforward and enriched exploration experience. By focusing on the needs of travellers and leveraging technology to provide timely and relevant information, this mobile application stands out as a practical and essential tool for modern explorers. Key Words: Navigations, Weather, Destination Insights, Accommodations, Dinnings, User Authentication.

AirLock: Unlock in-air via hand rotation recognition

This paper proposes AirLock, an artificial intelligence solution meticulously crafted to elevate user authentication security in network-aware environments. With a focus on enhancing safety and convenience within indoor spaces, AirLock ingeniously employs conventional multi-antenna commercial wireless systems as a supplementary security bolster. The system makes substantial contributions in two pivotal domains. Firstly, it adeptly utilizes amplitude differences between antenna pairs to extricate individual biometrics and seamlessly eliminate multipath noise from signals. Secondly, it boasts a Seq2Seq attention network structure fortified with a precise coding strategy for authentication, ensuring swift mapping of behavior characteristics to an authenticated user. Across diverse real-world scenarios, AirLock impressively achieves an average AAR of 96.5%.

A Proxy Re-Encryption Approach to Secure Data Sharing in the Internet of Things Based on Blockchain

The Internet of Things has seen data sharing as one of its most useful applications in cloud computing. As eye-catching as this technology has been, data security remains one of the obstacles it faces since the wrongful use of data leads to several damages. In this article, we propose a proxy re-encryption approach to secure data sharing in cloud environments. Data owners can outsource their encrypted data to the cloud using identity-based encryption, while proxy re-encryption construction will grant legitimate users access to the data. With the Internet of Things devices being resource-constrained, an edge device acts as a proxy server to handle intensive computations. Also, we make use of the features of information-centric networking to deliver cached content in the proxy effectively, thus improving the quality of service and making good use of the network bandwidth. Further, our system model is based on blockchain, a disruptive technology that enables decentralization in data sharing. It mitigates the bottlenecks in centralized systems and achieves fine-grained access control to data. The security analysis and evaluation of our scheme show the promise of our approach in ensuring data confidentiality, integrity, and security

Speckle visual cryptography for credential authentication

Based on the high random distribution characteristic of the natural speckle image, a new method of speckle visual cryptography, to the best of our knowledge, is designed by combining the natural speckle image with the secret key in visual cryptography. Specifically, we designed an authentication system for user credentials by combining speckle visual cryptography and the QR code. By using the speckle visual cryptography method, the image of the QR code carrying user authentication information is hidden in the speckle image, and the speckle image is printed on the paper credentials. Through a simulation and analog experiments, we verify the possibility of applying speckle visual cryptography to a user credentials authentication system, compare the improved grayscale reordering algorithm and grayscale reordering algorithm, and prove that the improved grayscale reordering algorithm has more advantages in this system by comparing the PSNR and SSIM. Finally, the y-interference ability and the uniqueness of the virtual secret key in the system are analyzed to prove that the secret key has high anti-interference ability and security.

Enhancing NOMA Network Security with RIS-UAV Integration: Exploring PPO Technique

In order to improve the security aspects of a nonorthogonal multiple access (NOMA) downlink network, we investigate the use of the proximal policy optimization (PPO) technique in this study. This network is uniquely augmented with reconfi- gurable intelligent surfaces (RIS) mounted on unmanned aerial vehicles (UAVs). The main objective of this article is to prevent possible eavesdroppers from accessing the network while still assuring continuous and secure connectivity for legitimate users. The network configuration includes a UAV outfitted with a RIS, which plays an important role in signal propagation. This work aims to increase the secrecy rates of all user communications in eavesdropping prone locations. By adaptively modifying the phase shifts and power distributions through the RIS the proposed PPO algorithm not only shows adaptability and effectiveness in securing wireless communications, but also highlights the significant advances made in communication system security through this technology.

AI-HybridChain: Picturized authentication and DRL based access control method with secure two fold revocation for ensuring cloud computing security

The Internet of Things is susceptible to seepage of private information during the data sharing. To circumvent this problem, access control and secure data sharing have been familiarized in cloud- IoT which is prevalent now days due to it storage and data access services. An intrusion detection implementation defends the veracity of the data sharing confining record are stored in a data base by recognizing when something changed unpredictably so that security and privacy are major anxieties. Therefore, it is crucial to develop the security apparatus that perceive and mitigate any feasible attack in cloud security services. In this paper, we proposed secure access control method with two-fold revocation for ensuring cloud computing security by hybrid blockchain (AI-Hybrid chain). Initially, all the users and services are registered their credentials to Secure Agent (SA) and provides image-based user authentication. Then, SA provides a long-term secret key which is generated by Improved Advanced Encryption Standard (IAES) algorithm, both user and service credentials are encrypted and stored in cloud chain. After that, gateway verifies the incoming requests are legitimate or illegitimate. For verifying the incoming packets, the proposed work utilizes Di-Fuzzy Inference System (Di-FIS) based on effective metrics. Further, legitimate request is optimally classified as sensitive and non-sensitive request for achieving secure service allocation using Tomtit Flock Optimization algorithm (TFO) based on optimal features. Once the service is allocated to users, we perform novel access control mechanism based on role and attribute of the users, the trust can be validated using Transfer Learning based Double Deep Q Network (TL-DDQN). Furthermore, virtual firewall is deployed in the cloud environment for analyzing the user storage request traffic as normal validated using Transfer Learning based Double Deep Q Network (TL-DDQN). Furthermore, virtual firewall is deployed in the cloud environment for analyzing the user storage request traffic as normal and malicious based on Contractive Residual Network (Con-ResNet). The implementation of proposed work is conducted by Network Simulator – 3.26 and the performance of the proposed AI-Hybrid chain model is itemized based on various performance metrics in terms of attack detection rate, overhead, success ratio, throughput, traffic rate, delay, response time and unauthorized access.

Simultaneous Authentication of Multiple Users Using a Single mmWave Radar

Simultaneous Authentication of Multiple Users Using a Single mmWave Radar

Fixed-text keystroke dynamics authentication data set—collection and analysis

AbstractKeystroke dynamics authentication is a method of authenticating a user and could be an alternative or addition to one-time codes, with minimal user inconvenience. In this study, a new data set was collected for 6 unique passwords, adding to the limited available data sets for keystroke dynamics available for researchers. Data was collected by emulating legitimate users familiar with the passwords and a wider range of attackers with limited login attempts. The data set is analyzed with the use of various methods, and the effects of password length and complexity are investigated. Two algorithms were employed, one achieving an average equal error rate varying between 10.2 and 18.1% depending on the password, and the other method achieving an average true accept rate of 98% and true reject rate of 90.4% by comparing across multiple individuals in the data set. These results provide a benchmark for further studies on this data set.

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.

ResNet1D-Based Personal Identification with Multi-Session Surface Electromyography for Electronic Health Record Integration.

Personal identification is an important aspect of managing electronic health records (EHRs), ensuring secure access to patient information, and maintaining patient privacy. Traditionally, biometric, signature, username/password, photo identity, etc., are employed for user authentication. However, these methods can be prone to security breaches, identity theft, and user inconvenience. The security of personal information is of paramount importance, particularly in the context of EHR. To address this, our study leverages ResNet1D, a deep learning architecture, to analyze surface electromyography (sEMG) signals for robust identification purposes. The proposed ResNet1D-based personal identification approach using the sEMG signal can offer an alternative and potentially more secure method for personal identification in EHR systems. We collected a multi-session sEMG signal database from individuals, focusing on hand gestures. The ResNet1D model was trained using this database to learn discriminative features for both gesture and personal identification tasks. For personal identification, the model validated an individual's identity by comparing captured features with their own stored templates in the healthcare EHR system, allowing secure access to sensitive medical information. Data were obtained in two channels when each of the 200 subjects performed 12 motions. There were three sessions, and each motion was repeated 10 times with time intervals of a day or longer between each session. Experiments were conducted on a dataset of 20 randomly sampled subjects out of 200 subjects in the database, achieving exceptional identification accuracy. The experiment was conducted separately for 5, 10, 15, and 20 subjects using the ResNet1D model of a deep neural network, achieving accuracy rates of 97%, 96%, 87%, and 82%, respectively. The proposed model can be integrated with healthcare EHR systems to enable secure and reliable personal identification and the safeguarding of patient information.