scholarly journals Secure Online Examination with Biometric Authentication and Blockchain-Based Framework

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiaoling Zhu ◽  
Chenglong Cao
Keyword(s):  
Access Control ◽  
Biometric Authentication ◽  
Fine Grained ◽  
Fuzzy Vault ◽  
Malicious Behavior ◽  
Online Examination ◽  
E Learning ◽  
Important Means ◽  
Biometric Templates ◽  
Biometric Features

E-learning has been carried out all over the world and then online examinations have become an important means to check learning effect during the outbreak of COVID-19. Participant authenticity, data integrity, and access control are the assurance to online examination. The existing online examination schemes cannot provide the protection of biometric features and fine-grained access control. Particularly, they did not discuss how to resolve some disputes among students, teachers, and a platform in a fair and reasonable way. We propose a novel biometric authentication and blockchain-based online examination scheme. The examination data are encrypted to store in a distributed system, which can be obtained only if the user satisfies decryption policy. And the pieces of evidence are recorded in a blockchain network which is jointly established by some credible institutions. Unlike other examination authentication systems, face templates in our scheme are protected using a fuzzy vault and a cryptographic method. Furthermore, educational administrative department can determine who the real initiator of malicious behavior is when a dispute arises using a dispute determination protocol. Analysis shows that no central authority is required in our scheme; the collusion of multiple users cannot obtain more data; even if the authorities compromise, biometric features of each user will not be leaked. Therefore, in terms of privacy-preserving biometric templates, fine-grained access, and dispute resolution, it is superior to the existing schemes.

scholarly journals Cancelable Multimodal Biometrics Based on Chaotic Maps

2021 ◽  
Vol 11 (18) ◽  
pp. 8573
Author(s):  
Sanaa Ghouzali ◽  
Ohoud Nafea ◽  
Abdul Wadood ◽  
Muhammad Hussain
Keyword(s):  
Chaotic Maps ◽  
Logistic Map ◽  
Biometric Authentication ◽  
Multimodal Biometrics ◽  
Biometric Systems ◽  
The Face ◽  
Systems Requirements ◽  
And Storage ◽  
Biometric Templates ◽  
Biometric Features

Biometric authentication systems raise certain concerns with regard to security, violation of privacy, and storage issues of biometric templates. This paper proposes a protection approach of biometric templates storage in a multimodal biometric system while ensuring both the cancelability of biometric templates and the efficiency of the authentication process. We propose applying a chaotic maps-based transform on the biometric features to address the cancelability issue. We used Logistic map and Torus Automorphism to generate cancelable biometric features of the face and fingerprint minutia points, respectively. Both transformed features would be concatenated and saved in the database of the system instead of the original features. In the authentication stage, the similarity scores of both transformed face and fingerprint templates are computed and fused using the weighted sum rule. The results of the experimentation, conducted using images from the ORL face and FVC2002 DB1 fingerprint databases, demonstrated the higher performance of the proposed approach achieving a genuine accept rate equal to 100%. Moreover, the obtained results confirmed the soundness of the proposed cancelable technique to satisfy the biometric systems’ requirements (i.e., security, revocability, and diversity).

Biometric Authentication Techniques and E-Learning

2019 ◽  
pp. 236-265 ◽  
Author(s):  
Ramgopal Kashyap
Keyword(s):  
Access Control ◽  
The State ◽  
The Body ◽  
Neural Systems ◽  
Biometric Authentication ◽  
E Learning ◽  
Physiological Attributes

The primary goal of this chapter is to answer online exam frameworks by utilizing face acknowledgment to verify students for going to an online exam. A strategy in light of the utilization of neural systems to validate individuals' computerized unique mark framework for e-learning is present. This chapter centers around breaking down and contrasting the distinctive facial verification frameworks to confirm the understudies when they utilize e-learning stages, itemizing the expenses and the highlights of each structure recorded. Biometrics is a sensible verification used as a type of distinguishing proof and access control. It is additionally used to distinguish people in bunches that are under observation. Biometric identifiers are then particular quantifiable qualities used to mark and portray people. Biometric authenticators are as often as possible named as conduct and additionally physiological attributes. Physiological qualities are identified with the state of the body. In this chapter, the essential focus is on the distinctive biometrics and their applications.

scholarly journals Privacy-Enhancing k-Nearest Neighbors Search over Mobile Social Networks

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3994
Author(s):  
Yuxi Li ◽  
Fucai Zhou ◽  
Yue Ge ◽  
Zifeng Xu
Keyword(s):  
Social Networks ◽  
Access Control ◽  
Location Privacy ◽  
Nearest Neighbors ◽  
Search Pattern ◽  
Broadcast Encryption ◽  
Mobile Social Networks ◽  
K Nearest Neighbors ◽  
Fine Grained ◽  
Server Architecture

Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive L-semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.

A fine-grained access control and revocation scheme on clouds

2012 ◽  
Vol 28 (6) ◽  
pp. 1697-1714 ◽  
Author(s):  
Shan-shan Tu ◽  
Shao-zhang Niu ◽  
Hui Li
Keyword(s):  
Access Control ◽  
Fine Grained
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