Multi-factor Authentication System Research Articles

Identity Based Authentication Scheme (IAS) for Securing WSN Based Internet of Things

The growing number of connected devices in IoT networks has raised security concerns. These networks face unique challenges, including limited resources, lack of standardized security protocols, and diverse devices and applications. Identity-based authentication is needed to address these threats and limitations. Implementing a multi-factor authentication system can enhance security and protect sensitive information from unauthorized access. The proposed Identity Based Authentication (IAS) scheme is implemented using the NS-2 simulator to address security challenges in IoT networks. Each node is assigned a unique identity for authentication, ensuring only authorized access and preventing security breaches. The IAS scheme enhances IoT network security by verifying node identities. Two scenarios are considered to evaluate the scalability and interoperability of the IAS scheme. The first scenario involves a random environment, assessing performance in real-world settings with varying device densities and network conditions. The second scenario involves a cluster-based environment, providing insights into the scheme's functionality and efficiency. By examining both scenarios, this research aims to provide a comprehensive understanding of how the authentication scheme performs in different deployment scenarios. The findings highlight the importance of selecting the appropriate authentication scheme based on the specific network environment and requirements. The superiority of the IAS authentication scheme suggests its potential for widespread adoption and implementation in various network scenarios over other authentication schemes.

Strengthening Multi-Factor Authentication Through Physically Unclonable Functions in PVDF-HFP-Phase-Dependent a-IGZO Thin-Film Transistors.

For enhanced security in hardware-based security devices, it is essential to extract various independent characteristics from a single device to generate multiple keys based on specific values. Additionally, the secure destruction of authentication information is crucial for the integrity of the data. Doped amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFTs) using poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) induce a dipole doping effect through a phase-transition process, creating physically unclonable function (PUF) devices for secure user information protection. The PUF security key, generated at VGS = 20V in a 20×10 grid, demonstrates uniformity of 42% and inter-Hamming distance (inter-HD) of 49.79% in the β-phase of PVDF-HFP. However, in the γ-phase, the uniformity drops to 22.5%, and inter-HD decreases to 35.74%, indicating potential security key destruction during the phase transition. To enhance security, a multi-factor authentication (MFA) system is integrated, utilizing five security keys extracted from various TFT parameters. The security keys from turn-on voltage (VON), VGS = 20V, VGS = 30V, mobility, and threshold voltage (Vth) exhibit near-ideal uniformities and inter-HDs, with the highest values of 58% and 51.68%, respectively. The dual security system, combining phase transition and MFA, establishes a robust protection mechanism for privacy-sensitive user information.

Multifactor Authentication System

The multifactor authentication system is a state- of-the-art solution created to improve security protocols across numerous sectors and shield confidential data from unauthorized access. Several layers of authentication are provided by this system, which makes use of cutting-edge technologies, ensuring that only people with the proper authorization can access particular resources or systems. It integrates biometric authentication, including fingerprint, facial, or iris scanning, which ups security because these biological characteristics are personal to each person. This system also uses multi-factor authentication, which combines two or more authentication factors, such as something the user is (a smart card), something they have (a password), or something they know (a password) (biometrics). This combination lessens the possibility of a single point of failure, hence enhancing security. Real-time monitoring, risk-based authentication, and behavioral biometrics are further aspects of the advanced authentication system that help to identify and stop fraudulent actions. Organizations can dramatically reduce security risks, safeguard sensitive data, and adhere to strict regulatory requirements by deploying this solution. The advancedauthentication system, in its whole, is a potent tool in the modern digital environment, protecting important assets with its strong and complex security measures. Keywords: advanced authentication system, security, biometric authentication, multi-factor authentication, real-time monitoring, risk- based authentication,

PREVENTION OF CYBER FRAUDS IN THE BANKING SECTOR

The project under study explores the prevention of cyber fraud in the banking sector. With the rise of digital banking and increasing cyber threats, it is crucial to identify effective measures to combat cyber fraud and protect the integrity of the banking system. The key strategies for prevention, include education and awareness, technology solutions, fraud detection, and monitoring, as well as collaboration and regulatory measures. Educating customers and bank employees about cyber fraud risks, implementing multi-factor authentication systems, utilizing encryption techniques, and employing anomaly detection algorithms are some of the preventive measures discussed. The project emphasizes the importance of collaboration between banks, law enforcement agencies, and cybersecurity organizations to enhance information sharing and response to cyber threats. Strengthening regulatory frameworks and imposing strict penalties are also identified as crucial steps in promoting cybersecurity practices and deterring cyber criminals. By understanding and implementing these preventive measures, the banking sector can mitigate the risks associated with cyber fraud and safeguard customer assets and data. Key Words: — Banking, Cyber security, Cyber Fraud detection, Finance, Institution, Clients, Customer, Prevention, Research, Collaboration, Interdisciplinary, Strategies, Measures,

A Literature Survey on Personalized AI-Based Voice Assistant for Authentication

This literature review critically examines the evolving landscape of personalized AI-based voice assistants in the realm of authentication services, The review begins with an exploration of the development and nuanced functionalities of voice recognition technologies, emphasizing their integration in multi-factor authentication systems. It delves into the synergistic relationship between voice and facial recognition technologies, highlighting advancements and challenges in biometric authentication, including accuracy, user experience, and security vulnerabilities.A significant focus is placed on the role of AI in personalizing user interactions with authentication services, where adaptive learning and contextual awareness are pivotal.The review also addresses the enduring relevance of traditional security measures, such as secure PIN’s, and their interplay with biometric methods to fortify authentication processes.The economic and commercial implications of these technologies are explored, considering their impact on business models and market trends.This comprehensive review identifies gaps in the current research landscape and suggests potential directions for future inquiry, particularly in enhancing security measures and improving user-centric designs. It aims to provide a holistic understanding of the current state and future potential of personalized AI-based voice assistants in authentication services, offering valuable insights for researchers and practitioners in the field. Key Words: Voice Recognition Technologies, Facial Recognition, Multimodal Authentication, Secure PINs, Biometric Authentication.

VISUAL CRYPTOGRAPHY: STRENGTHENING BANKING AUTHENTICATION WITH IMAGE PROCESSING

In today's digital era, we present a multi-factor authentication system that combines Visual Cryptography, Face Authentication, and OTP Verification to fortify banking security. Visual Cryptography splits images into secure shares, Face Authentication verifies unique facial features, and OTP Verification adds an extra layer. The synergy of these factors forms a robust, secure, and user- friendly system, reducing unauthorized access and fraud. This project contributes to cyber-security advancements and improves the banking user experience. In an ever-growing digital banking landscape, this innovative approach ensures data confidentiality and addresses evolving threats. Keywords: Visual Cryptography, Image Processing, Face Recognition, Encryption, Multi-factor Authentication

A Secure and Efficient Biometric Template Protection Scheme for Palmprint Recognition System

The accuracy and security of a biometric system are the two sides of a coin. A biometric system must be simple, flexible, efficient, and secure enough from unauthorized access. Concerning these requirements, this paper presents an enhanced palmprint recognition system with superior performance and improved biometric template protection schemes. This method comprises five components: image preprocessing, feature extraction, cancelable biometrics, classification, and Bio-cryptosystem. The palm texture region is extracted from the input hand image during preprocessing. A feature representation technique is then used to extract discriminant features from the palmprint texture patterns. The extracted features are then analyzed using an information coding scheme to compute a user-specific token. Here, the user-specific tokens along with the original palmprint features are used to calculate the feature vectors for the cancelable biometric system. A novel Bio-Cryptosystem has been proposed to protect templates with high security where there is no need to remember the users&#x2019; tokens. Cancelable feature vectors are kept online in encrypted form using the proposed Bio-Cryptosystem, which is used to identify or verify the subjects after decryption. The original feature vectors are kept offline to prevent these from external attacks and misuse. Finally, the multi-class linear support vector machine has been used for user classification. For experimental purposes, two benchmark hand image databases: BOSPHORUS and CASIA-Palmprint, are employed, and the proposed system has achieved nearly 100&#x0025; correct recognition rate in cancelable domain for both the employed databases. Finally, the performance comparison in terms of both verification and identification for the palmprint and the cancelable palmprint recognition systems with the existing state-of-the-art methods shows the superiority of the proposed system. <i>Impact Statement</i> &#x2014;We have improved the biometric template protection scheme by modifying the cancelable biometric technique with two security levels capable of protecting the biometric information from the dictionary, brute-force, database, channel, replay, and spoofing attacks. To avoid the difficulty of remembering long user passwords/tokens, an automatic key generation technique of user passwords has been proposed. Two different keys are generated: the first one used for cancelable biometrics and the second for encryption-decryption processes. Both these keys are not needed to store or remember and are helpful for a multi-factor authentication system. A novel Bio-cryptographic algorithm instead of traditional Bio-Cryptographic algorithms have been introduced within the proposed system. Several attacks and challenging issues of biometric recognition systems have been considered with maintaining outstanding performance in terms of accuracy and security.

Analysis of Distinguishable Security between the One-Time Password Extraction Function Family and Random Function Family

A one-time password is a security system that uses a password that is only used once for authentication, and it is commonly used in multi-factor authentication systems. The process of generating an OTP is very similar to generating pseudorandom sequences in cryptography. However, since only a part of the bit string is used in OTP, an algorithm is needed to extract that part. In addition, the OTP process also includes converting the value of the bit string value into decimal form for human perception. This paper focuses on analyzing the extraction function, which is the step before the hexadecimal is reprocessed into the decimal form. We analyze a function family, which includes functions used in the process of extracting a bit string in terms of distinguishable security. As a result, we conclude that the OTP extraction function family is vulnerable in terms of distinguishable security compared to the random function family.

A Novel Authentication Method That Combines Honeytokens and Google Authenticator

Despite the rapid development of technology, computer systems still rely heavily on passwords for security, which can be problematic. Although multi-factor authentication has been introduced, it is not completely effective against more advanced attacks. To address this, this study proposes a new two-factor authentication method that uses honeytokens. Honeytokens and Google Authenticator are combined to create a stronger authentication process. The proposed approach aims to provide additional layers of security and protection to computer systems, increasing their overall security beyond what is currently provided by single-password or standard two-factor authentication methods. The key difference is that the proposed system resembles a two-factor authentication but, in reality, works like a multi-factor authentication system. Multi-factor authentication (MFA) is a security technique that verifies a user’s identity by requiring multiple credentials from distinct categories. These typically include knowledge factors (something the user knows, such as a password or PIN), possession factors (something the user has, such as a mobile phone or security token), and inherence factors (something the user is, such as a biometric characteristic like a fingerprint). This multi-tiered approach significantly enhances protection against potential attacks. We examined and evaluated our system’s robustness against various types of attacks. From the user’s side, the system is as friendly as a two-factor authentication method with an authenticator and is more secure.

Investigating Perceived Security and Usability of Secure Shield: An Advanced Multi-Factor Authentication System - A Survey

The multi-step multi-factor authentication (MFA) procedure for logging into an account demands more information from users to authenticate the users. The paper presents a comprehensive literature review and analysis of Secure Shield, an advanced multi-factor authentication system that incorporates facial recognition and momentum. Here we explore the effectiveness of multi-factor authentication in enhancing online security and address the limitations of traditional password-based systems. Facial recognition offers a convenient and robust biometric authentication factor, while the addition of momentum adds an extra layer of security by capturing facial movements. The discussion section highlights the implications of these findings for online security and suggests further research directions. Overall, this paper contributes to the understanding of Secure Shield as an advanced multi-factor authentication system, highlighting its potential in strengthening online security and mitigating risks associated with traditional password-based systems.

Ensuring Information System Security by Selective Multifactor Authentication / Обеспечение безопасности информационных систем с помощью выборочной многофакторной аутентификации

Multi-factor Authentication (MFA) has emerged as an important security measure to protect sensitive information and prevent unauthorized access in an increasingly interconnected world. In this article, we introduced the multi-factor authentication system we developed, which is a security mechanism and not only offers multiple authentication methods for users to verify their identity, but does it all in a clearly fixed order, which increases the level of security on vulnerable websites and minimizes the loss of accounts. This toolkit is flexible in its structure and can be used both separately and as an integral system. One of the advantages is that users themselves choose the authentication system and their order. All this slightly complicates the authentication process, but guarantees security from cyber attacks.

A Study on Establishing a DID-based Defense Multi-Factor Authentication(MFA) System

A Study on Establishing a DID-based Defense Multi-Factor Authentication(MFA) System

Multifactor Authentication System Using Simplified EEG Brain–Computer Interface

This article proposes a scheme for multifactor authentication based on electroencephalography (EEG) signal analysis. A solution for EEG signal acquisition and recording of acquisition results has been implemented, a machine learning model has been developed and trained, then a classifier that determines the user's login procedure familiarity has been built, and a solution to carry out the described experiments has been implemented, in the form of a mobile application. Besides, a multifactor authentication system, based on the EEG signal combined with user image verification, using the brain–computer interface system with a single EEG electrode based on the NeuroSky MindWave device was proposed. Based on the defined scenarios, experiments were conducted, followed by a survey on the research group, and the obtained results were analyzed. In the case of an experiment related to login simulation, a high classification accuracy rate was obtained, both for the classifier itself (83.33%) and the proposed user authentication system (77.78%). Analyzing the results of the EEG signal recording used in the classification, it seems that the proposed solution is promising not only due to the high accuracy and a low false rejections rate but also through confirmed associations in the analysis of brain wave signal, corresponding to the results of research in the literature. A proposed multi-factor authentication system based on image selection and EEG analysis can be implemented in many areas as a modern solution in securing IT systems.

A Study on Three Step Multifactor Authentication System for Modern Security

Abstract: This survey paper reviews all the major factors in validating three-level passwords such as one-factor authentication using passwords and two-factor authentication is not enough to provide better security to the modern digital age with remarkable advances in the field of information technology. Even when single-factor or two-factor authentication was used to secure remote access and the system, hacking tools, were simple computer programs for collecting private keys, as well as private generators have made it difficult to provide security. Security threats based on malware, such as important installed trackers, are always available to improve security risks. This is necessary the use of a safe and easy-to-use object. As a result, Three Level Security is an easy-to-use software. It also proves the use of different techniques used by different authors. Keywords: Three-level authentication, network, security, remote access, two-factor authentication

ChestLive

Voice-based authentication is prevalent on smart devices to verify the legitimacy of users, but is vulnerable to replay attacks. In this paper, we propose to leverage the distinctive chest motions during speaking to establish a secure multi-factor authentication system, named ChestLive. Compared with other biometric-based authentication systems, ChestLive does not require users to remember any complicated information (e.g., hand gestures, doodles) and the working distance is much longer (30cm). We use acoustic sensing to monitor chest motions with a built-in speaker and microphone on smartphones. To obtain fine-grained chest motion signals during speaking for reliable user authentication, we derive Channel Energy (CE) of acoustic signals to capture the chest movement, and then remove the static and non-static interference from the aggregated CE signals. Representative features are extracted from the correlation between voice signal and corresponding chest motion signal. Unlike learning-based image or speech recognition models with millions of available training samples, our system needs to deal with a limited number of samples from legitimate users during enrollment. To address this problem, we resort to meta-learning, which initializes a general model with good generalization property that can be quickly fine-tuned to identify a new user. We implement ChestLive as an application and evaluate its performance in the wild with 61 volunteers using their smartphones. Experiment results show that ChestLive achieves an authentication accuracy of 98.31% and less than 2% of false accept rate against replay attacks and impersonation attacks. We also validate that ChestLive is robust to various factors, including training set size, distance, angle, posture, phone models, and environment noises.

Improving the covertness in the physical-layer authentication

A well-designed Physical-Layer Authentication (PLA) scheme should consider three properties: covertness, robustness, and security. However, the three properties always cause some dilemmas, e.g., higher covertness leading to lower robustness. This paper concerns the problem of improving the covert- ness without sacrificing the robustness. This problem is important because of the following reasons: reducing the errors in recovered source message, improving the security, and ease of constructing a multi-factor authentication system. In this paper, we propose three covert PLA schemes to address the problem. In the first scheme, we improve the covertness by reducing the modification ratio on the source message based on an encoding mechanism. In the second scheme, we improve the covertness by optimizing the superimposing angle, which maximizes the minimum distance between the tagged symbols and the boundary line of the demodulation decision for the source message. In the third scheme, referred to as the hybrid scheme, we further improve the covertness by jointly using the advantages of both the above two schemes. Our experimental results show that when the SNR at a legitimate receiver is 25 dB, as compared with the prior scheme, the first scheme improves the covertness by 17.74%, the second scheme improves the covertness by 28.79%, and the third scheme improves the covertness by 32.09%, while they have similar robustness as that of the prior scheme.

How to Use Bit-string Representation of the Face in a Multi-factor Authentication System

How to Use Bit-string Representation of the Face in a Multi-factor Authentication System

ExpressionHash: Securing Telecare Medical Information Systems Using BioHashing

The COVID-19 outbreak and its medical distancing phenomenon have effectively turned the global healthcare challenge into an opportunity for Telecare Medical Information Systems. Such systems employ the latest mobile and digital technologies and provide several advantages like minimal physical contact between patient and healthcare provider, easy mobility, easy access, consistent patient engagement, and cost-effectiveness. Any leakage or unauthorized access to users’ medical data can have serious consequences for any medical information system. The majority of such systems thus rely on biometrics for authenticated access but biometric systems are also prone to a variety of attacks like spoofing, replay, Masquerade, and stealing of stored templates. In this article, we propose a new cancelable biometric approach which has tentatively been named as “Expression Hash” for Telecare Medical Information Systems. The idea is to hash the expression templates with a set of pseudo-random keys which would provide a unique code (expression hash). This code can then be serving as a template for verification. Different expressions would result in different sets of expression hash codes, which could be used in different applications and for different roles of each individual. The templates are stored on the server-side and the processing is also performed on the server-side. The proposed technique is a multi-factor authentication system and provides advantages like enhanced privacy and security without the need for multiple biometric devices. In the case of compromise, the existing code can be revoked and can be directly replaced by a new set of expression hash code. The well-known JAFFE (The Japanese Female Facial Expression) dataset has been for empirical testing and the results advocate for the efficacy of the proposed approach.

Exploring Half-Duplex Communication of NFC Read/Write Mode for Secure Multi-Factor Authentication

Near Field Communication (NFC) is a prominent short-range, contact-less communication technology, which is rapidly getting popular in modern smart devices. For communication between two active devices via NFC, applications generally choose the peer-to-peer operation mode. In this paper, we exploit the possibility of using the NFC read/write mode, designed primarily for unidirectional data transfer from an active NFC reader to a passive NFC tag, for bi-directional half-duplex communication between two active NFC devices. The advantages of using the NFC read/write mode include low protocol overhead and permitting different data formats. However, the challenges are avoiding the reader collision problem, maintaining a secure session, and completing all transactions in an acceptable time frame. In this paper, we address the above challenges and propose a methodology for efficient communication between active NFC devices using NFC read/write mode. To evaluate the scheme, we design a secure Multi-Factor Authentication (MFA) system that requires bi-directional communication for mutually authenticating two NFC devices. The proposed methodology is experimentally verified using NFC-enabled Android smartphones and a Kerberos server as the third-party authenticator.

Security Enhancement of an Automated Teller Machine Using Fingerprint and Password

This paper focuses on how to enhanced security of Transactions in Automatic Teller Machine system using a multi-factor authentication system (Password and Fingerprint). In order to achieve security and to overcome illegal activities, shortcoming of piracy in money transactions, we propose the idea of using fingerprints of customers and password instead of traditional use of PIN number. After authorized verification, the customer will be able to proceed for transaction else after four successive wrong attempts, the ATM card will be ejected automatically and a message will be sent to the registered mobile number. The proposed system is developed to provide better security to the ATMs. Keywords— ATM, Fingerprint, PIN, Biometric.