PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation

doi:10.3837/tiis.2020.07.011

Cited by 3 publications

(4 citation statements)

References 36 publications

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“…Approaches for generating cryptographic key from biometrics have considered various biometric traits, such as fingerprint [12][13][14][15][16][17] finger vein [18], iris [19], face [20,21], voice [22], handwritten signature [23], gait [24][25][26][27], ECG [28,29], retina [30] and multi-modal [31][32][33].…”

Section: Fig 1 Generation Of Cryptographic Keys From Biometricsmentioning

confidence: 99%

“…In the majority of the above approaches, cryptographic key (or part of it) is obtained by the binary encoding of decimal values (e.g., principal component [20], length and angle ratio [14], the Euclidean distances [15,16]). In binary codebased approaches, small variations in these values have the maximum effects on the generated key bit strings.…”

Section: Fig 1 Generation Of Cryptographic Keys From Biometricsmentioning

confidence: 99%

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Two-factor-based RSA key generation from fingerprint biometrics and password for secure communication

Suresh

Pal

Balasundaram

2022

Complex Intell. Syst.

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In an asymmetric-key cryptosystem, the secure storage of private keys is a challenging task. This paper proposes a novel approach for generating the same public and private key pair on a need basis. Hence, the need for secure storage of the private key is done away with. The proposed approach for generating the key pair is based on two factors: fingerprint biometrics and password. A stable binary string is generated from the distances among pairs of minutiae points in a fingerprint using a gray code-based method. Experiments show that gray code representation significantly reduces the number of inconsistencies between the generated bit strings from two instances of the same fingerprint as against the binary code representation. Hence, the Reed–Solomon error correction code successfully corrects errors due to variations in multiple instances of the same fingerprint to induce stability in the generated string. Hash of the stable string generated from the fingerprint and the string generated from hashed password are XORed to derive a stable seed value. The proposed approach uses this seed value to generate two large prime numbers. These prime numbers are used to generate the public and private key pair using the RSA key generation method. This seed value ensures the generation of the same key pair every time. The experimental results show that the proposed approach can ensure a stable generation of the key. It is not required to store either the fingerprint template or the password. Moreover, the generated private key is also not stored. It can be regenerated on a need basis.

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Section: Fig 1 Generation Of Cryptographic Keys From Biometricsmentioning

confidence: 99%

Section: Fig 1 Generation Of Cryptographic Keys From Biometricsmentioning

confidence: 99%

Two-factor-based RSA key generation from fingerprint biometrics and password for secure communication

Suresh

Pal

Balasundaram

2022

Complex Intell. Syst.

View full text Add to dashboard Cite

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“…1.Building group category in real-time QoS matrix data. User group category and service group category are obtained by Principal Component Analysis (PCA) [24] and K-means algorithm. And the information of group category is used to modeling a new regularization term in matrix factorization model.…”

Section: Introductionmentioning

confidence: 99%

An expanded Matrix Factorization model for real-time Web service QoS prediction

2021

KSII TIIS

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Real-time prediction of Web service of quality (QoS) provides more convenience for web services in cloud environment, but real-time QoS prediction faces severe challenges, especially under the cold-start situation. Existing literatures of real-time QoS predicting ignore that the QoS of a user/service is related to the QoS of other users/services. For example, users/services belonging to the same group of category will have similar QoS values. All of the methods ignore the group relationship because of the complexity of the model. Based on this, we propose a real-time Matrix Factorization based Clustering model (MFC), which uses category information as a new regularization term of the loss function. Specifically, in order to meet the real-time characteristic of the real-time prediction model, and to minimize the complexity of the model, we first map the QoS values of a large number of users/services to a lower-dimensional space by the PCA method, and then use the K-means algorithm calculates user/service category information, and use the average result to obtain a stable final clustering result. Extensive experiments on real-word datasets demonstrate that MFC outperforms other state-of-the-art prediction algorithms.

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“…Aeyoung Kim et al [33] proposed a secret key prevention technique for any third party using multivariate biometric key functions. A short key is generated for a specific use only with principal component analysis and confidence interval analysis techniques.…”

mentioning

confidence: 99%

AAAA: SSO and MFA Implementation in Multi-Cloud to Mitigate Rising Threats and Concerns Related to User Metadata

Hussain

Zhu

et al. 2021

Applied Sciences

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In the modern digital era, everyone is partially or fully integrated with cloud computing to access numerous cloud models, services, and applications. Multi-cloud is a blend of a well-known cloud model under a single umbrella to accomplish all the distinct nature and realm requirements under one service level agreement (SLA). In current era of cloud paradigm as the flood of services, applications, and data access rise over the Internet, the lack of confidentiality of the end user’s credentials is rising to an alarming level. Users typically need to authenticate multiple times to get authority and access the desired services or applications. In this research, we have proposed a completely secure scheme to mitigate multiple authentications usually required from a particular user. In the proposed model, a federated trust is created between two different domains: consumer and provider. All traffic coming towards the service provider is further divided into three phases based on the concerned user’s data risks. Single sign-on (SSO) and multifactor authentication (MFA) are deployed to get authentication, authorization, accountability, and availability (AAAA) to ensure the security and confidentiality of the end user’s credentials. The proposed solution exploits the finding that MFA achieves a better AAAA pattern as compared to SSO.

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PCA-CIA Ensemble-based Feature Extraction for Bio-Key Generation

Cited by 3 publications

References 36 publications

Two-factor-based RSA key generation from fingerprint biometrics and password for secure communication

Two-factor-based RSA key generation from fingerprint biometrics and password for secure communication

An expanded Matrix Factorization model for real-time Web service QoS prediction

AAAA: SSO and MFA Implementation in Multi-Cloud to Mitigate Rising Threats and Concerns Related to User Metadata

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