Existing Authentication Systems Research Articles

Mouse Dynamics Behavioral Biometrics: A Survey

Utilization of the Internet in our everyday lives has made us vulnerable in terms of privacy and security of our data and systems. Therefore, there is a pressing need to protect our data and systems by improving authentication mechanisms, which are expected to be low cost, unobtrusive, and ideally ubiquitous in nature. Behavioral biometric modalities such as mouse dynamics (mouse behaviors on a graphical user interface (GUI)) and widget interactions (another modality closely related to mouse dynamics that also considers the target (widget) of a GUI interaction, such as links, buttons, and combo-boxes) can bolster the security of existing authentication systems because of their ability to distinguish individuals based on their unique features. As a result, it can be difficult for an imposter to impersonate these behavioral biometrics, making them suitable for authentication. In this article, we survey the literature on mouse dynamics and widget interactions dated from 1897 to 2023. We begin our survey with an account of the psychological perspectives on behavioral biometrics. We then analyze the literature along the following dimensions: tasks and experimental settings for data collection, taxonomy of raw attributes, feature extractions and mathematical definitions, publicly available datasets, algorithms (statistical, machine learning, and deep learning), data fusion, performance, and limitations. We end the paper with presenting challenges and promising research opportunities.

Innovations in Multi-Factor Authentication: Exploring OAuth for Enhanced Security

In an era where digital security breaches are becoming increasingly sophisticated, multi-factor authentication (MFA) has emerged as a critical defense mechanism to protect sensitive data and systems. OAuth (Open Authorization) has gained prominence as an advanced protocol in the landscape of MFA, offering enhanced security through its token-based authorization model. This paper explores innovations in multi-factor authentication with a particular focus on OAuth, analyzing its effectiveness, implementation challenges, and the benefits it brings to modern security frameworks. OAuth operates as a protocol that provides secure delegated access to applications without exposing user credentials. Traditionally, MFA combines multiple forms of authentication, such as passwords, biometric data, and hardware tokens, to verify user identity. OAuth enhances this process by enabling secure, token-based access, which minimizes the risks associated with credential theft and phishing attacks. By allowing users to authorize third-party applications to access their data on their behalf, OAuth reduces the need for users to share their passwords with multiple services, thereby mitigating potential security threats. The adoption of OAuth in MFA strategies introduces several innovations. Firstly, it supports the use of access tokens that are short-lived and specific to particular resources or actions. This temporary nature of tokens limits the impact of a potential breach, as compromised tokens have a limited lifespan. Secondly, OAuth incorporates scopes, which define the exact permissions granted to a third party. This granular control over access rights ensures that applications only receive the minimum level of access necessary, further reducing security risks. Implementing OAuth for MFA, however, is not without its challenges. One major issue is the complexity of integrating OAuth with existing authentication systems. Organizations must ensure that OAuth tokens are securely generated, transmitted, and validated to prevent unauthorized access. Additionally, the secure management of refresh tokens, which are used to obtain new access tokens, is crucial to maintaining the integrity of the authentication process. The need for rigorous token management practices and robust security measures is essential to prevent potential vulnerabilities. Despite these challenges, the benefits of incorporating OAuth into MFA strategies are significant. OAuth enhances user experience by allowing single sign-on (SSO) capabilities, reducing the need for users to remember multiple passwords. This streamlined approach not only improves user convenience but also strengthens security by minimizing password-related vulnerabilities. Moreover, OAuth's support for various authentication factors, including biometric verification and hardware tokens, allows organizations to implement a comprehensive MFA strategy that aligns with their security requirements. The evolution of OAuth in MFA represents a significant advancement in the field of digital security. By leveraging OAuth’s token-based model, organizations can enhance their authentication processes, reduce the risk of credential-related attacks, and provide a more secure user experience. As cybersecurity threats continue to evolve, the integration of OAuth into MFA strategies will play a pivotal role in safeguarding sensitive information and ensuring the integrity of digital interactions.

Encoded-image-based authentication utilizing diffractive-imaging scheme and secret-key-assisted phase retrieval

Traditional optical encryption and authentication systems required complex holographic setups to capture complex-valued wavefronts. To address this limitation and create more compact architectures, there is growing interest in combining phase retrieval algorithms (PRAs) with optical authentication. However, most of the existing authentication systems based on PRAs heavily rely on random phase masks for encryption, which raises security concerns. In this paper, a secure method for encoded-image-based authentication is proposed, utilizing a diffractive-imaging scheme and secret-key-assisted phase retrieval. The method employs a simplified optical diffractive-imaging scheme to encrypt an input secret image and an aperture, resulting in the generation of a noise-like image for authentication. Both the encoded image for authentication and the aperture key are essential for decryption and authentication. The decryption process employs a secret-key-assisted phase retrieval algorithm within the framework of diffractive-imaging-based encryption. This work provides an alternative approach to authenticate users by utilizing a noise-like image and an aperture key. By providing an enlarged key space and enabling authentication without visual disclosure of the secret image, this method ensures a high level of security. Simulation results validate the feasibility and effectiveness of the proposed method.

PressPIN: Enabling Secure PIN Authentication on Mobile Devices via Structure-Borne Sounds

PIN authentication is widely used on mobile devices due to its usability and simplicity. However, it is known to be susceptible to shoulder surfing attacks, where an adversary spies the user’s PIN by direct human observation or camera-based recording. This paper proposes PressPIN, a novel enhanced PIN authenticator on mobile devices by sensing pressures from the user’s finger. Since pressure-sensitive touch screens are unavailable on most phones, we leverage the structure-borne propagation of sounds to estimate the pressure on the screen. When the user inputs the PINs, the pressure is extracted from each number to form the <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> -bit pressure code, where <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> corresponds to the length of the PIN sequence. The pressure code is difficult to be inferred by snooping or videotaping, and increases the entropy of passwords. In this way, PressPIN provides a low-cost, user-friendly, and more secure solution resistant to shoulder surfing attacks. Our extensive experiments with 30 participants and three types of smartphones demonstrate that PressPIN can authenticate legitimate users with high accuracy (e.g., as high as 96.7% within two trials), and is robust to various types of attacks (e.g., only 2.5% attack success rate even when the adversary can observe the legitimate user’s PIN sequence and finger pressing clearly). Additionally, PressPIN requires no additional hardware (e.g., the pressure sensor) and can be readily integrated into existing authentication systems of mobile devices.

Development of Miniaturized Wearable Wristband Type Surface EMG Measurement System for Biometric Authentication

Personal authentication systems employing biometrics are attracting increasing attention owing to their relatively high security compared to existing authentication systems. In this study, a wearable electromyogram (EMG) system that can be worn on the forearm was developed to detect EMG signals and, subsequently, apply them for personal authentication. In previous studies, wet electrodes were attached to the skin for measuring biosignals. Wet electrodes contain adhesives and conductive gels, leading to problems such as skin rash and signal-quality deterioration in long-term measurements. The miniaturized wearable EMG system developed in this study comprised flexible dry electrodes attached to the watch strap, enabling EMG measurements without additional electrodes. In addition, for accurately classifying and applying the measured signal to the personal authentication system, an optimal algorithm for classifying the EMG signals based on a multi-class support vector machine (SVM) model was implemented. The model using cubic SVM achieved the highest personal authentication rate of 87.1%. We confirmed the possibility of implementing a wearable authentication system by measuring the EMG signal and artificial intelligence analysis algorithm presented in this study.

FPGA implementation of fast & secure fingerprint authentication using trsg (true random and timestamp generator)

In the digital authentication system, the emerging technology is fingerprint authentication, which have been concentrated more attraction towards security and control. Existing authentication systems such as Biometric cryptosystems, Cancellable templates, and Bio-hashing provide a solution for addressing these vulnerabilities. To implement the fingerprint authentication with more accuracy, a novel FPGA based authentication system has proposed in this paper and the performance has evaluated with the help of the previous scheme. First, finger code template (FCT) is generated by applying transformation function on finger code and biometric key created from the randomization process. While in the second phase, 40-bit binary string (ofc), 40-bit binary time stamp, random numbers 0 and 40 (r1, r2, r3, and r4) are generated from TRSG (True Random and Time Stamp Generator) which is converted into 80-bit efc. Based on the obtained efc, the person details are compared with primary data stored in the database. The simulation result shows that the proposed method reduces the LUT utilization to 0.17% and complexity as 14%. Hence, FPGA based fingerprint authentication shows its excellence with the lowest complexity value and thereby enhance the presentation of the biometric authentication system.

Fingerprint Presentation Attack Detection Using Transfer Learning Approach

In this busy world, biometric authentication methods are serving as fast authentication means. But with growing dependencies on these systems, attackers have tried to exploit these systems through various attacks; thus, there is a strong need to protect authentication systems. Many software and hardware methods have been proposed in the past to make existing authentication systems more robust. Liveness detection/presentation attack detection is one such method that provides protection against malicious agents by detecting fake samples of biometric traits. This paper has worked on fingerprint liveness detection/presentation attack detection using transfer learning for which the authors have used a pre-trained NASNetMobile model. The experiments are performed on publicly available liveness datasets LivDet 2011 and LivDet 2013 and have obtained good results as compared to state of art techniques in terms of ACE(average classification error).

Secure Banking Transaction using Encryption Based Negative Password Scheme

Password authentication is the most widely used authentication technique, for it is available at a low cost and easy to deploy. Many users usually set their passwords using familiar vocabulary for its convenience to remember. Passwords may be leaked from weak systems. Vulnerabilities are continuously being determined, and no longer all systems may be well timed patched to resist attacks, which give adversaries an opportunity to illegally access vulnerable systems. To overcome the vulnerabilities of password attacks, here propose a password authentication framework that is designed for secure password storage and could be easily integrated into existing authentication systems. In our framework, first, the received plain password from a client is hashed through a cryptographic hash function (e.g., SHA-512). Then, the hashed password is randomly shuffled to get a negative password. Finally, the negative password is encrypted into an Encrypted Negative Password using a symmetric-key algorithm RC5, to further improve security. The proposed hash function and encryption methodologies make it difficult to break passwords from ENPs. This proposed ENP system will be implemented for banking environment to improve security of password storage and transaction details.

Eye gesture blink password: a new authentication system with high memorable and maximum password length

Authentication systems in which eye is used for entering the password are categorized into two gaze-based and gesture-based groups. In the accurate point-of-regard gaze measurements, a key subject with gaze-based authentication schemes is needed. Gesture-based systems are based on identifying the eye movement tracking, hence, there is no need to estimate the precise point of the user’s vision. Although gesture-based systems are superior to gaze-based methods, they are not appropriate and applicable in remembering the equivalent gesture of any suitable number due to the high memory overhead. This paper introduces the new Eye Gesture Blink Password authentication system (EGBP). The system is based on four basic ideas: system design, the algorithm of finding fixations without having to track pupils in all frames, allowing users to blink as part of the password and the new method of finding the user password using the angle formed between the fixations. EGBP has several basic advantages compared to existing authentication systems including the no need for a commercial eye tracker that lowers the system’s cost, removing the calibration step that increases the speed and requires less processing, and choosing a maximum length code that reduces the likelihood of the likeness of the selected password and increases security. The possibility of simply memorizing the password because of the possibility of blinking and user’s high-speed input is another advantage of this system.

Authentication by Encrypted Negative Password

Secure password storage is a vital aspect in systems based on password authentication, which is still the most widely used authentication technique, despite some security flaws. In this paper, we propose a password authentication framework that is designed for secure password storage and could be easily integrated into existing authentication systems. In our framework, first, the received plain password from a client is hashed through a cryptographic hash function (e.g., SHA-256). Then, the hashed password is converted into a negative password. Finally, the negative password is encrypted into an encrypted negative password (ENP) using a symmetric-key algorithm (e.g., AES), and multi-iteration encryption could be employed to further improve security. The cryptographic hash function and symmetric encryption make it difficult to crack passwords from ENPs. Moreover, there are lots of corresponding ENPs for a given plain password, which makes precomputation attacks (e.g., lookup table attack and rainbow table attack) infeasible. The algorithm complexity analyses and comparisons show that the ENP could resist lookup table attack and provide stronger password protection under dictionary attack. It is worth mentioning that the ENP does not introduce extra elements (e.g., salt); besides this, the ENP could still resist precomputation attacks. Most importantly, the ENP is the first password protection scheme that combines the cryptographic hash function, the negative password, and the symmetric-key algorithm, without the need for additional information except the plain password.

Multimodal biometric hashkey cryptography based authentication and encryption for advanced security in cloud

Cloud Computing (CC) is a technology that is growing at a faster pace, gaining much popularity with startup companies increasing and opting for clouds’ services. The growth rate of this technology is high and so is the security threat. Though there are existing authentication systems like two factor authentication, biometric based authentication and so on, hackers still pose greater challenges. Though password-based authentication system is simple, it is highly vulnerable to security breaches. Biometric based authentication has better security, but usage of single biometric traits can also be easily compromised. Thus, this research work, Multimodal Biometric Hashkey Cryptography (MBHC) brings about a novel security framework that focuses on both authentication and securing cloud data using multiple modalities. Authentication is based on multiple biometric modalities viz. Fingerprint, Iris and Face features. Features from these modalities are extracted using linear filters. Artificial Fish Swarm Algorithm (AFSA) is used for feature optimization, further to which Support Vector Machine (SVM) acts as classifier for identifying genuine users against imposters. Cryptographic keys are generated from these modalities that serve as input to Advanced Encryption Standard (AES) Algorithm for encrypting and decrypting the information stored in cloud. Integrity of data is also ensured using hash function for which the facial features and the encrypted message are the inputs. Thus, the experimental results show that the proposed architecture provides improved security for cloud computing environment when compared to the existing models.

Inhibiting and Detecting Offline Password Cracking Using ErsatzPasswords

In this work, we present a simple, yet effective and practical scheme to improve the security of stored password hashes, increasing the difficulty to crack passwords and exposing cracking attempts. We utilize a hardware-dependent function (HDF), such as a physically unclonable function (PUF) or a hardware security module (HSM), at the authentication server to inhibit offline password discovery. Additionally, a deception mechanism is incorporated to alert administrators of cracking attempts. Using an HDF to generate password hashes hinders attackers from recovering the true passwords without constant access to the HDF. Our scheme can integrate with legacy systems without needing additional servers, changing the structure of the hashed password file, nor modifying client machines. When using our scheme, the structure of the hashed passwords file, e.g., etc/shadow or etc/master.passwd , will appear no different than traditional hashed password files. 1 However, when attackers exfiltrate the hashed password file and attempt to crack it, the passwords they will receive are ErsatzPasswords—“fake passwords.” The ErsatzPasswords scheme is flexible by design, enabling it to be integrated into existing authentication systems without changes to user experience. The proposed scheme is integrated into the pam_unix module as well as two client/server authentication schemes: Lightweight Directory Access Protocol (LDAP) authentication and the Pythia pseudorandom function (PRF) Service [Everspaugh et al. 2015]. The core library to support ErsatzPasswords written in C and Python consists of 255 and 103 lines of code, respectively. The integration of ErsatzPasswords into each explored authentication system required less than 100 lines of additional code. Experimental evaluation of ErsatzPasswords shows an increase in authentication latency on the order of 100ms, which maybe acceptable for real world systems. We also describe a framework for implementing ErsatzPasswords using a Trusted Platform Module (TPM).

Avoiding the Tsunami

The internet has enabled new business models which have the potential to fundamentally change the economy [25]. The basic driver–the ability to operate at zero marginal costs–has also influenced the dark economy. Attacks operated at zero marginal costs can easily be scaled out to millions of attack targets and justify high initial investments while still being “profitable” for attackers. Existing authentication systems are too weak or they are not designed to work at internet scale.

A Fine-Grained Analysis of User Activity on Mobile Applications: The Sensitivity Level Perception

Mobile devices contain different levels of data and applications such as photos, text messages, emails and mobile banking applications. Each process within each application has a different level of sensitivity; thus, protection needs to be considered in this context after initial access to the mobile device. The main aim of this research is to investigate when to authenticate the mobile user by focusing on the sensitivity level of each intra-process (within the application) and understanding whether a certain user action in a process may require protection. To accomplish this, the 10 most popular mobile categories were analysed to gain a comprehensive understanding of how to categorise the applications in terms of their sensitivity level. Building upon this analysis, the results show that 78% of 125 user actions are considered sensitive processes. This paper also demonstrates that existing authentication systems lack adequate security solutions to unauthorised access to the mobile device. Consequently, this indicates the need for a robust and usable access control approach to establish a transparent and a continuous authentication system.

Analysis of existing authentication systems of information and communication systems and networks

This article analyzes patterns of authentication in modern information and communication systems and networks. As a result, the analysis highlighted the advantages and disadvantages of the existing templates to provide protection. Select the most efficient in terms of differentiation and control of access to information resources.

Upgrading a ColdFusion-Based Academic Medical Library Staff Intranet

This article details the process of upgrading and expanding an existing academic medical library intranet to include a wiki, blog, discussion forum, and photo collection manager. The first version of the library's intranet from early 2002 was powered by ColdFusion software and existed primarily to allow staff members to author and store minutes of library team meetings. Other ColdFusion-based applications and functions were subsequently added, as were various other library documents and procedures. As a follow-up to the library's strategic plan, a library Staff Intranet Team was organized in early 2008 to reorganize the content of the intranet and to identify software tools that would allow greater staff participation in maintaining and updating intranet content. Early steps in the process included brainstorming, a card-sorting exercise, product research, a staff survey, and paper prototyping. The team focused on implementing various open-source, ColdFusion-based tools in order to accommodate existing technology, available budget, and time constraints. Challenges in implementing the tools included bypassing or modifying existing authentication systems and applying modifications that led to loss of native functionality. Despite usability testing and staff training, library staff have not universally welcomed or adopted all the new tools. Notwithstanding these challenges, the renovated staff intranet has shown promise in furthering the goals in the library's strategic plan to improve communication and facilitate collaboration among library staff.