Biometric cryptosystems: Open issues and challenges

Karimovich, Ganiyev Salim; Turakulovich, Khudoykulov Zarif

doi:10.1109/icisct.2016.7777408

Cited by 14 publications

(3 citation statements)

References 4 publications

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“…Databases is very important part in holding information in our day present day digital [14]. Security measures in databases encompass various techniques aimed at maintaining the quality, trust, and availability of information [15]. In [16], several methods for maintaining database security are proposed, including physical security, network security, password access control, biometric authentication, data encryption, auditing, and logging.…”

Section: Review Of Related Literaturementioning

confidence: 99%

A novel hybrid database security management technique

Margaret Dumebi Okpor,

Kizito Eluemunor Anazia,

Daniel Ukpenusiowho

2024

Int. J. Sci. Res. Arch.

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Since the advent of the internet and the digitization of information, more individuals and organizations have gained access to the internet, leading to a significant expansion in the size of our database systems. These databases are relied upon for day-to-day activities by individuals and organizations. Furthermore, the advancements in technology have increased the vulnerability of database management systems and enforcing adequate database security measures is of paramount importance to individuals and organizations. In this study, we deployed a hybrid approach to database security system that integrates two techniques: dynamic time-warping algorithm and voice recognition methods. The implementation follows Object-Oriented Analysis and Design procedures, utilizing SQL Management Studio 2014 for the backend and ASP.NET C# for the frontend. Our hybrid approach demonstrates enhanced database security compared to previously employed authentication measures.

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Section: Review Of Related Literaturementioning

confidence: 99%

A novel hybrid database security management technique

Margaret Dumebi Okpor,

Kizito Eluemunor Anazia,

Daniel Ukpenusiowho

2024

Int. J. Sci. Res. Arch.

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“…One challenge is the need for accurate voice recognition. Voice characteristics can vary due to factors such as age, health conditions, background noise, or changes in speaking style [8,9]. Banks need to ensure that their voice biometric systems are robust enough to accurately identify and authenticate customers under different conditions consistently.…”

Section: Srinivas Publicationmentioning

confidence: 99%

ABCD Analysis of Voice Biometric System in Banking

M. K.,

Aithal

2024

IJMTS

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Purpose: This article aims to provide an overview of the voice biometric system in banking and its benefits using the ABCD analytical methodology. Voice biometric systems in banking are pivotal for improving customer experiences, effortlessly integrating into various service channels like call centers and mobile apps. This article provides advantages, benefits, constraints and disadvantages (ABCD) analysis of the voice biometric offerings for banking sector. Design/Methodology/Approach: The research examined published papers through the ABCD analysis framework, employing quantitative analysis within focus group interactions to uncover crucial attributes and variables that impact consumers' intentions to implement voice biometric system in banking system. This process yielded valuable insights. Findings/Result: The ABCD analytical approaches of voice biometric systems in banking indicates the enhanced customer satisfaction and streamline operations through their diverse functionalities. When integrated into the bank's multi-factor authentication framework, voice biometric systems serve as a non-intrusive yet highly secure authentication method. They offer a seamless customer experience by eliminating the need for traditional PINs or passwords, reducing the risk of unauthorized access, and bolstering overall system security. The implementation of voice biometric systems in the banking sector provides several key benefits. Originality/Value: Utilizing the ABCD analysis approach, this research examines the inclination of consumers to activate the voice biometric systems in banking. The investigation delves into consumer behavior and the elements that impact usage decisions, employing determinant issues, key attributes, factor analysis, and elementary analysis. Paper Type: Empirical Analysis

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“…The proposed approach is used to improve security and privacy Many researchers have explored different approaches to solve these issues. The traditional bio-key generation scheme is divided into three categories [5,6]: key binding, key generation, and secure sketch and fuzzy extractor, which face the following challenges:…”

Section: Introductionmentioning

confidence: 99%

A Secure Biometric Key Generation Mechanism via Deep Learning and Its Application

Wang

Zhang

et al. 2021

Applied Sciences

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Biometric keys are widely used in the digital identity system due to the inherent uniqueness of biometrics. However, existing biometric key generation methods may expose biometric data, which will cause users’ biometric traits to be permanently unavailable in the secure authentication system. To enhance its security and privacy, we propose a secure biometric key generation method based on deep learning in this paper. Firstly, to prevent the information leakage of biometric data, we utilize random binary codes to represent biometric data and adopt a deep learning model to establish the relationship between biometric data and random binary code for each user. Secondly, to protect the privacy and guarantee the revocability of the biometric key, we add a random permutation operation to shuffle the elements of binary code and update a new biometric key. Thirdly, to further enhance the reliability and security of the biometric key, we construct a fuzzy commitment module to generate the helper data without revealing any biometric information during enrollment. Three benchmark datasets including ORL, Extended YaleB, and CMU-PIE are used for evaluation. The experiment results show our scheme achieves a genuine accept rate (GAR) higher than the state-of-the-art methods at a 1% false accept rate (FAR), and meanwhile satisfies the properties of revocability and randomness of biometric keys. The security analyses show that our model can effectively resist information leakage, cross-matching, and other attacks. Moreover, the proposed model is applied to a data encryption scenario in our local computer, which takes less than 0.5 s to complete the whole encryption and decryption at different key lengths.

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Biometric cryptosystems: Open issues and challenges

Cited by 14 publications

References 4 publications

A novel hybrid database security management technique

A novel hybrid database security management technique

ABCD Analysis of Voice Biometric System in Banking

A Secure Biometric Key Generation Mechanism via Deep Learning and Its Application

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