Authentication Process Research Articles

Password based Smart Doorlock System using Arduino UNO for Enhanced Security

In recent years, the demand for secure access systems has increased significantly, especially in residential and commercial areas. Hence, this presents the design and implementation of a password-based door lock system using an Arduino microcontroller and a servo motor. The system provides a cost-effective and reliable solution for managing access to physical sites. The proposed system uses an Arduino microcontroller as the central device to control the authentication process and to control the servo motor that operates the door locking mechanism. A matrix keyboard is used to enter the password, which provides a user-friendly interface for communication. The servo motor is responsible for physically locking and unlocking the door mechanism based on the authentication result. The operational workflow of the system requires the user to enter a predetermined password using a keyboard. The Arduino microcontroller compares the entered password with the password stored in its memory. After successful authentication, a servo motor is operated to open the door, allowing access to the authorized person. Conversely, failed authentication will result in access being denied.

Auth4App: Streamlining authentication for integrated cyber–physical environments

The growing integration of mobile applications for user authentication has revolutionized user interactions with digital platforms, offering novel possibilities in user experience (UX). However, this paradigm shift poses significant security challenges. Leveraging smartphones for authentication purposes provides convenient and swift access to services, streamlining user interactions with various platforms through simple taps. Several institutions adopt static QR Codes generated from primary, unchanging user data (e.g., individual citizen national identification numbers) for physical authentication procedures like access turnstiles. However, relying on static data introduces critical security vulnerabilities as this data is susceptible to compromise. Implementing an One-Time Authentication Code (OTAC) approach appears promising in addressing these issues. Nevertheless, the absence of an integrated solution for developing a physical authentication process using OTAC leads to suboptimal API user experiences (UX APIs) and subsequent security vulnerabilities. In response to this challenge, we introduce Auth4App, a protocol set designed for identification and authentication using mobile applications. Auth4App comprises two core protocols: one dedicated to linking user credentials to mobile devices (i.e., identification), and the other for generating OTAC. We showcase the adaptability and practicality of Auth4App through three distinct case studies: a mobile-only scenario, integration of mobile devices with a turnstile, and integration of Auth4App with FIDO2. To ensure the robustness of the security protocols, Auth4App is evaluated using automated verification tools and argument proofs, solidifying the system’s reliability.

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.

Modeling security evaluation framework for IoHT-driven systems using integrated decision-making methodology

The intensification of the Internet of Health Things devices created security concerns due to the limitations of these devices and the nature of the healthcare data. While dealing with the security challenges, several authentication schemes, protocols, processes, and standards have been adopted. Consequently, making the right decision regarding the installation of a secure authentication solution or procedure becomes tricky and challenging due to the large number of security protocols, complexity, and lack of understanding. The major objective of this study is to propose an IoHT-based assessment framework for evaluating and prioritizing authentication schemes in the healthcare domain. Initially, in the proposed work, the security issues related to authentication are collected from the literature and consulting experts’ groups. In the second step, features of various authentication schemes are collected under the supervision of an Internet of Things security expert using the Delphi approach. The collected features are used to design suitable criteria for assessment and then Graph Theory and Matrix approach applies for the evaluation of authentication alternatives. Finally, the proposed framework is tested and validated to ensure the results are consistent and accurate by using other multi-criteria decision-making methods. The framework produces promising results such as 93%, 94%, and 95% for precision, accuracy, and recall, respectively in comparison to the existing approaches in this area. The proposed framework can be picked as a guideline by healthcare security experts and stakeholders for the evaluation and decision-making related to authentication issues in IoHT systems

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.

Hybrid cryptography-based scheme with conditional privacy-preserving authentication and memory-based DOS resilience in V2X

To secure Vehicle-to-everything (V2X) communications, many Conditional Privacy-Preserving Authentication schemes (CPPA) use symmetric and asymmetric encryption during the authentication process. However, several existing schemes have some security limitations regarding VANET requirements. In many symmetric cryptography-based schemes, the participants are required to share the same keys which could compromise the security of the network in case the key of one participant is compromised, while many asymmetric cryptography-based schemes take much time during the authentication process, and don't address the denial-of-service attack. In this paper, we propose a certificateless scheme that does not require a certificate and prevents the escrow problem. Plus, it uses the elliptic curve cryptography and avoids bilinear pairing and Map-to-Hash functions. We call our scheme Hybrid Cryptography-Based Scheme with a Conditional Privacy-Preserving Authentication (HCBS-CPPA), as it uses both symmetric and asymmetric cryptography during the authentication process. Our scheme combines the strength of an asymmetric encryption that satisfies non-repudiation, and the strength of a symmetric encryption that allows to perform a lightweight authentication. In addition, we show that our scheme is resilient to memory-based Denial of Service (DOS) attack which occurs when an attacker floods the memory of a receiver with invalid messages. A security proof shows that HCBS-CPPA is secure in the random oracle. Regarding the simulation of our scheme, it turns out that HCBS-CPPA has the best performance when compared with several existing certificateless schemes. Additionally, it requires less execution time during the signing and verification process, as well as less communication overhead when compared to the existing schemes.

Revolutionizing Identity Verification and Recognition

The innovative integration of real-time human detection improves both security and user experience in identity authentication. This approach improves authentication processes by analysing physiological and behavioural indicators such as face movements and eye movements, hence reducing fraud risks. Its deployment across sectors promises to enhance security in finance, healthcare, e-commerce, and law enforcement. Despite the hurdles, the benefits of this human-centered approach are enormous, indicating a more secure digital future. Keywords— Identity verification, live human detection, digital security, biometric authentication, user experience, fraud prevention, computer vision, physiological and behavioural cues, facial and vocal patterns, finance, healthcare, e-commerce, law enforcement.

Fingerprint authentication based on deep convolutional descent inversion tomography

Fingerprint authentication is widely used in various areas. While existing methods effectively extract and match fingerprint features, they encounter difficulties in detecting wet fingers and identifying false minutiae. In this paper, a fast fingerprint inversion and authentication method based on Lamb waves is developed by integrating deep learning and multi-scale fusion. This method speeds up the inversion performance through deep fast inversion tomography (DeepFIT) and uses Mask R-CNN to improve authentication accuracy. DeepFIT utilizes fully connected and convolutional operations to approach the descent gradient, enhancing the efficiency of ultrasonic array reconstruction. This suppresses artifacts and accelerates sub-millimeter-level fingerprint minutia inversion. By identifying the overall morphological relationships of various minutia in fingerprints, meaningful minutia representing individual identities are extracted by the Mask R-CNN method. It segments and matches multi-scale fingerprint features, improving the reliability of authentication results. Results indicate that the proposed method has high accuracy, robustness, and speed, optimizing the entire fingerprint authentication process.

Citizens’ Perception of Blockchain-Based E-Voting Systems: Focusing on TAM

Digital transformation and new technologies have made people’s lives easier and led to great results in most areas of business and society. Implementing blockchain technology is one of the best tools for establishing sustainable smart cities and societies. In terms of sustainable governance sophisticated and secure voting systems are necessary to achieve high integrity and transparency and null election fraud, and, in environmental sustainability, e-voting systems eliminate the mass waste of paper and transportation gas emissions; namely, e-voting systems are eco-friendly with high democratic outcomes. Blockchain technology can revolutionize e-voting by increasing the security and transparency of the voting process. Integrating artificial intelligence (AI) and machine learning (ML) into blockchain-based e-voting systems further augments their effectiveness. AI algorithms can analyze voting patterns and detect irregularities, supporting the prevention of fraudulent activities and coercion. ML procedures can enhance voter authentication processes, improve accessibility for diverse demographics, and optimize the productivity of blockchain networks during peak voting periods. This study focuses on understanding citizen perceptions of blockchain-based e-voting in a smart city context using the Technology Acceptance Model (TAM). The study’s results indicate that perceived ease of use and perceived usefulness are important factors in determining citizens’ intentions to use blockchain-based e-voting. Furthermore, trust in the technology and perceived security were found to influence the usefulness of blockchain-based e-voting positively. This study provides important insights for policymakers and technologists seeking to promote the adoption of blockchain-based e-voting systems in smart cities. The findings of the research supported the research model with positive results. In conclusion, our research model encourages the adoption of a blockchain-based e-voting system to enhance the future voting environment.

MAG-PUFs: Authenticating IoT devices via electromagnetic physical unclonable functions and deep learning

The challenge of authenticating Internet of Things (IoT) devices, particularly in low-cost deployments with constrained nodes that struggle with dynamic re-keying solutions, renders these devices susceptible to various attacks. This paper introduces a robust alternative mitigation strategy based on Physical-Layer Authentication (PLA), which leverages the intrinsic physical layer characteristics of IoT devices. These unique imperfections, stemming from the manufacturing process of IoT electronic integrated circuits (ICs), are difficult to replicate or falsify and vary with each function executed by the IoT device. We propose a novel lightweight authentication scheme, MAG-PUFs, that uses the unintentional Electromagnetic (EM) emissions from IoT devices as Physical Unclonable Functions (PUFs). MAG-PUFs operate by collecting these unintentional EM emissions during the execution of pre-defined reference functions by the IoT devices. The authentication is achieved by matching these emissions with profiles recorded at the time of enrollment, using state-of-the-art Deep Learning (DL) approaches such as Neural Networks (NN) and Autoencoders. Notably, MAG-PUFs offer compelling advantages: (i) it preserves privacy, as it does not require direct access to the IoT devices; and, (ii) it provides unique flexibility, permitting the selection of numerous and varied reference functions. We rigorously evaluated MAG-PUFs using 25 Arduino devices and a diverse set of 325 reference function classes. Employing a DL framework, we achieved a minimum authentication F1-Score of 0.99. Furthermore, the scheme’s efficacy in detecting impostor EM emissions was also affirmed, achieving a minimum F1-Score of 0.99. We also compared our solution to other solutions in the literature, showing its remarkable performance. Finally, we discussed code obfuscation techniques and the impact of Radio Frequency (RF) interference on the IoT authentication process.

NDNOTA: NDN One-Time Authentication

Named Data Networking (NDN) stands out as a prominent architectural framework for the future Internet, aiming to address deficiencies present in IP networks, specifically in the domain of security. Although NDN packets containing requested content are signed with the publisher’s signature which establishes data provenance for content, the NDN domain still requires more holistic frameworks that address consumers’ identity verification while accessing protected contents or services using producer/publisher-preapproved authentication servers. In response, this paper introduces the NDN One-Time Authentication (NDNOTA) framework, designed to authenticate NDN online services, applications, and data in real time. NDNOTA comprises three fundamental elements: the consumer, producer, and authentication server. Employing a variety of security measures such as single sign-on (SSO), token credentials, certified asymmetric keys, and signed NDN packets, NDNOTA aims to reinforce the security of NDN-based interactions. To assess the effectiveness of the proposed framework, we validate and evaluate its impact on the three core elements in terms of time performance. For example, when accessing authenticated content through the entire NDNOTA process, consumers experience an additional time overhead of 70 milliseconds, making the total process take 83 milliseconds. In contrast, accessing normal content that does not require authentication does not incur this delay. The additional NDNOTA delay is mitigated once the authentication token is generated and stored, resulting in a comparable time frame to unauthenticated content requests. Additionally, obtaining private content through the authentication process requires 10 messages, whereas acquiring public data only requires two messages.

Cloud Service Authentication Based On Advanced Encryption Standard (AES) For Ensure Privacy

Considering the possible consequences of illegal access, cloud service authentication privacy must be guaranteed. Negative actors might get access to private information without the right authentication procedures, which could result in monetary losses, harm to one’s reputation, and legal repercussions. This paper proposed using the advanced encryption standard (AES) algorithm for cloud service authentication to guarantee privacy and alleviate these problems. Providing a safe and effective authentication process that ensures user data privacy is the main goal of this framework. To encrypt user credentials and other authentication related data before sending it to the cloud service provider, the proposed framework makes use of the AES algorithm. With the use of an encryption key, the data is rendered unintelligible even in the event that it is intercepted. In order to guard against man in the middle attacks and eavesdropping, the authentication system also includes secure key exchange protocols and secure communication routes. Organizations may feel secure and in control of their data stored in the cloud by implementing this cloud service authentication architecture. It provides a strong barrier against breaches of privacy, illegal access, and data breaches. A workable and efficient way to guarantee privacy and safeguard sensitive data is to employ the AES algorithm for cloud service authentication. Through the use of this framework, businesses may take use of cloud computing’s advantages while retaining control over their data and lowering the danger of illegal access.

A Blockchain-Based Privacy Preserving Intellectual Property Authentication Method

With the continuous advancement of information technology, a growing number of works, including articles, paintings, and music, are being digitized. Digital content can be swiftly shared and disseminated via the Internet. However, it is also vulnerable to malicious plagiarism, which can seriously infringe upon the rights of creators and dampen their enthusiasm. To protect creators’ rights and interests, a sophisticated method is necessary to authenticate digital intellectual property rights. Traditional authentication methods rely on centralized, trustworthy organizations that are susceptible to single points of failure. Additionally, these methods are prone to network attacks that can lead to data loss, tampering, or leakage. Moreover, the circulation of copyright information often lacks transparency and traceability in traditional systems, which leads to information asymmetry and prevents creators from controlling the use and protection of their personal information during the authentication process. Blockchain technology, with its decentralized, tamper-proof, and traceable attributes, addresses these issues perfectly. In blockchain technology, each node is a peer, ensuring the symmetry of information. However, the transparent feature of blockchains can lead to the leakage of user privacy data. Therefore, this study designs and implements an Ethereum blockchain-based intellectual property authentication scheme with privacy protection. Firstly, we propose a method that combines elliptic curve cryptography (ECC) encryption with digital signatures to achieve selective encryption of user personal information. Subsequently, an authentication algorithm based on Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARK) is adopted to complete the authentication of intellectual property ownership while encrypting personal privacy data. Finally, we adopt the InterPlanetary File System (IPFS) to store large files, solving the problem of blockchain storage space limitations.

Surveying Authentication and Authorization Mechanisms in Today's Web Technology Landscape

This paper presents a comprehensive survey of authentication and authorization mechanisms in contemporary web technology. It examines the diverse approaches and frameworks employed to secure web systems and protect user data. Beginning with an overview of fundamental concepts such as authentication methods and access control models, the paper explores the landscape of authentication and authorization in depth. It evaluates the effectiveness and limitations of various authentication methods, including passwords, biometrics, and multifactor authentication (MFA). Additionally, the paper scrutinizes authorization mechanisms such as role-based access control (RBAC), attribute-based access control (ABAC), and policy-based access control (PBAC). Through a systematic review of integration frameworks like OAuth and OpenID Connect, it assesses their role in facilitating secure authentication and authorization processes. Furthermore, the paper analyzes emerging trends and innovations in authentication and authorization practices, providing insights into the future direction of web security. By synthesizing existing research and identifying key challenges and opportunities, this survey paper aims to inform researchers, practitioners, and policymakers about the state-of-the-art in authentication and authorization mechanisms and guide future developments in web security.

Examining the Intersection of Prophetic Hadith and Intellect: Authenticity, Contradiction, and Scholarly Perspectives

This article critically examines the question of whether a prophetic Hadith can be considered weak if it conflicts with intellect. The research employs analytical and library research methods, drawing on a range of scholarly works including books, academic articles, and writings by Muslim scholars spanning both the classical and contemporary eras.This study reveals that when the authenticity of a Hadith is uncertain and it contradicts intellect, it can be deemed weak. However, if a Hadith is deemed authentic by Hadith scholars despite its contradiction with intellect, two distinct theories emerge among Muslim scholars. The first theory, supported by many classical scholars and their contemporary followers, argues that a correct Hadith never opposes the intellect. According to this perspective, a sound and clear intellect will never contradict an authentic Hadith. In contrast, the second theory, advocated by modern Muslim scholars and some classical scholars, posits that a prophetic Hadith should be considered weak if it conflicts with intellect.The findings of this paper indicate that a prophetic Hadith, when narrated through a strong chain of narrators tracing back to the Prophet Muhammad, cannot inherently contradict the intellect. However, if a Hadith contradicts sound intellect, it can serve as a valid reason to question its authenticity and consider it weak. Through a comprehensive analysis of the scholarly discourse surrounding this topic, this study provides a deeper understanding of the complex relationship between prophetic Hadith and intellect. It underscores the importance of rigorous authentication processes, emphasizing the need to consider the reliability of the Hadith chain and the principles of intellectual reasoning when assessing the strength or weakness of a prophetic Hadith

Secure and Scalable Internet of Things Model Using Post-Quantum MACsec

For the secure deployment of network platforms tailored for IoT devices, the encryption of data transmission is equally as crucial as the process of authentication. In this context, we introduce the Secure and Scalable IoT network (SSI) network platform, designed to accommodate a diverse range of IoT devices. It provides scalability and implements effective many-to-many and end-to-end encryption across extensive regions. With the emergence of quantum computing, secure public key exchange mechanisms have become important. Among the various post-quantum cryptography (PQC) algorithms assessed, Nth Degree Truncated Polynomial Ring Units (NTRUs) have emerged as an optimally suited PQC algorithm for IoT devices constrained by limited computational capabilities. We have integrated NTRUs with SSI as a lightweight PQC solution. Moreover, SSI-PQM (Post-Quantum MACsec) enhances the SSI’s initial authentication structure to minimize PQC-TLS session attempts and protect the SSI’s important configuration information. When applying TLS with PQC for secret key exchange purposes, it was verified that this approach ensures stable performance in IoT environments. Upon the implementation of our proposed SSI-PQM on Raspberry Pi 3B+ based IoT devices, SSI-PQM exhibited acceptable performance at security levels from 80 to 128 and achieved a minimum speed improvement of 161% over RSA at security levels above 160. It can be concluded that SSI-PQM stands out as an effective Zero Trust-based IoT network platform, demonstrating its viability and efficiency in safeguarding data transmission against potential quantum computing threats.

Comprehensive Person Profiling System

The proposed Comprehensive person profiling system aims to use innovative approach to revolutionizing identity verification in financial transactions, particularly within banks or other financial organizations. This project aims to replace traditional national ID usage with a more efficient and secure system. Leveraging advanced technologies such as biometrics, data analytics, and machine learning, the system ensures a comprehensive profiling of individuals, offering a robust alternative to conventional identification methods. By seamlessly integrating into financial institutions, this solution enhances inconveniences of the users’ doing transactions, security, minimizes identity fraud, and streamlines customer authentication processes. The Comprehensive Person Profiling System not only safeguards sensitive information but also enhances the overall efficiency and reliability of financial transactions, marking a significant leap towards a more secure and technologically advanced future in the realm of personal identification.

BPA: A Novel Blockchain-Based Privacy-Preserving Authentication Scheme for the Internet of Vehicles

The Internet of Vehicles (IoV) connects an isolated individual on the road to share information, which can improve traffic efficiency. However, the promotion of information sharing brings the critical security issues of identity authentication, followed by privacy protection issues in the authentication process in the IoV. In this study, we designed a blockchain-based conditional privacy-preserving authentication scheme for the IoV (BPA). Our scheme implements zero-knowledge proof (ZKP) to verify the identities of vehicles, which moves the authentication process down to the Roadside Units (RSUs) and achieves decentralized authentication at the edge nodes. Moreover, blockchain technology is utilized to synchronize a consistent ledger across all RSUs for recording and disseminating vehicle authentication states, which enhances the overall authentication process efficiency. We provide a theoretical analysis asserting that the BPA ensures enhanced security and effectively protects the privacy of all participating vehicles. Experimental evaluations confirm that our scheme outperforms existing solutions in terms of the computational and communication overhead.

Performance of security options for message protocols: A comparative analysis

AbstractWe explore the challenges around security configuration and performance while utilizing publish–subscribe protocols in the Internet of Things, edge computing, and fog computing. Issues in security configuration can lead to disruptions and higher operation costs. These issues can be prevented by selecting the appropriate transmission technology for each configuration, considering the variations in sizing, installation, sensor profile, distribution, security, networking, and locality. We introduce a comparative analysis of different configurations around a smart agriculture use case. For that, we implemented a simulation environment to generate datasets relevant to research and compare the results in terms of performance, resource utilization, security, and resilience—focused on authentication process. This analysis provides a blueprint to decision support for fog computing engineers on the best practices around security configurations.

Aadhar Based Biometric Electronic Voting System

Flawless voting is guaranteed through the use of Electronic Voting Machines. It is crucial for citizens to have confidence in the security of their votes and to prevent any fraudulent activities. The primary objective of this initiative is to create a secure Electronic Voting Machine that utilizes fingerprint identification technology. To access fingerprints, the AADHAR card database is utilized. During elections, the authentication process for e-voting involves finger vein sensing, which allows voters to cast their votes after electronic ballot reset. Furthermore, the voting data and details of voters can be transmitted to the nearby Database Administration unit via WIFI. The fingerprint scanning feature is implemented to ensure security and prevent issues like fake or repeated voting. This system not only improves accuracy but also enhances the speed of the voting process