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  • Open Access

    ARTICLE

    Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

    Puja S. Prasad1, Adepu Sree Lakshmi1, Sandeep Kautish2, Simar Preet Singh3, Rajesh Kumar Shrivastava3, Abdulaziz S. Almazyad4, Hossam M. Zawbaa5, Ali Wagdy Mohamed6,7,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 725-739, 2024, DOI:10.32604/cmes.2023.030640

    Abstract Pupil dynamics are the important characteristics of face spoofing detection. The face recognition system is one of the most used biometrics for authenticating individual identity. The main threats to the facial recognition system are different types of presentation attacks like print attacks, 3D mask attacks, replay attacks, etc. The proposed model uses pupil characteristics for liveness detection during the authentication process. The pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light intensities. The proposed framework consists of two-phase methodologies. In the first phase, the pupil’s diameter is calculated by applying… More >

  • Open Access

    ARTICLE

    Iris Recognition Based on Multilevel Thresholding Technique and Modified Fuzzy c-Means Algorithm

    Slim Ben Chaabane1,2,*, Rafika Harrabi1,2, Anas Bushnag1, Hassene Seddik2

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 201-214, 2022, DOI:10.32604/jai.2022.032850

    Abstract Biometrics represents the technology for measuring the characteristics of the human body. Biometric authentication currently allows for secure, easy, and fast access by recognizing a person based on facial, voice, and fingerprint traits. Iris authentication is one of the essential biometric methods for identifying a person. This authentication type has become popular in research and practical applications. Unlike the face and hands, the iris is an internal organ, protected and therefore less likely to be damaged. However, the number of helpful information collected from the iris is much greater than the other biometric human organs.… More >

  • Open Access

    ARTICLE

    Biometric Finger Vein Recognition Using Evolutionary Algorithm with Deep Learning

    Mohammad Yamin1,*, Tom Gedeon2, Saleh Bajaba3, Mona M. Abusurrah4

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5659-5674, 2023, DOI:10.32604/cmc.2023.034005

    Abstract In recent years, the demand for biometric-based human recognition methods has drastically increased to meet the privacy and security requirements. Palm prints, palm veins, finger veins, fingerprints, hand veins and other anatomic and behavioral features are utilized in the development of different biometric recognition techniques. Amongst the available biometric recognition techniques, Finger Vein Recognition (FVR) is a general technique that analyzes the patterns of finger veins to authenticate the individuals. Deep Learning (DL)-based techniques have gained immense attention in the recent years, since it accomplishes excellent outcomes in various challenging domains such as computer vision,… More >

  • Open Access

    ARTICLE

    Robust and Reusable Fuzzy Extractors from Non-Uniform Learning with Errors Problem

    Joo Woo1, Jonghyun Kim1, Jong Hwan Park2,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1985-2003, 2023, DOI:10.32604/cmc.2023.033102

    Abstract A fuzzy extractor can extract an almost uniform random string from a noisy source with enough entropy such as biometric data. To reproduce an identical key from repeated readings of biometric data, the fuzzy extractor generates a helper data and a random string from biometric data and uses the helper data to reproduce the random string from the second reading. In 2013, Fuller et al. proposed a computational fuzzy extractor based on the learning with errors problem. Their construction, however, can tolerate a sub-linear fraction of errors and has an inefficient decoding algorithm, which causes the reproducing time… More >

  • Open Access

    ARTICLE

    Voice Response Questionnaire System for Speaker Recognition Using Biometric Authentication Interface

    Chang-Yi Kao1, Hao-En Chueh2,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 913-924, 2023, DOI:10.32604/iasc.2023.024734

    Abstract

    The use of voice to perform biometric authentication is an important technological development, because it is a non-invasive identification method and does not require special hardware, so it is less likely to arouse user disgust. This study tries to apply the voice recognition technology to the speech-driven interactive voice response questionnaire system aiming to upgrade the traditional speech system to an intelligent voice response questionnaire network so that the new device may offer enterprises more precise data for customer relationship management (CRM). The intelligence-type voice response gadget is becoming a new mobile channel at the

    More >

  • Open Access

    ARTICLE

    A Proposed Biometric Authentication Model to Improve Cloud Systems Security

    Hosam El- El-Sofany1,2,*

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 573-589, 2022, DOI:10.32604/csse.2022.024302

    Abstract Most user authentication mechanisms of cloud systems depend on the credentials approach in which a user submits his/her identity through a username and password. Unfortunately, this approach has many security problems because personal data can be stolen or recognized by hackers. This paper aims to present a cloud-based biometric authentication model (CBioAM) for improving and securing cloud services. The research study presents the verification and identification processes of the proposed cloud-based biometric authentication system (CBioAS), where the biometric samples of users are saved in database servers and the authentication process is implemented without loss of the… More >

  • Open Access

    ARTICLE

    Real-Time Multimodal Biometric Authentication of Human Using Face Feature Analysis

    Rohit Srivastava1, Ravi Tomar1, Ashutosh Sharma2, Gaurav Dhiman3, Naveen Chilamkurti4, Byung-Gyu Kim5,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1-19, 2021, DOI:10.32604/cmc.2021.015466

    Abstract As multimedia data sharing increases, data security in mobile devices and its mechanism can be seen as critical. Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time. Humans incorporate physiological attributes like a fingerprint, face, iris, palm print, finger knuckle print, Deoxyribonucleic Acid (DNA), and behavioral qualities like walk, voice, mark, or keystroke. The main goal of this paper is to design a robust framework for automatic face recognition. Scale Invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF) are employed for face recognition. Also, we propose a… More >

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