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  • Open Access

    ARTICLE

    Novel Multimodal Biometric Feature Extraction for Precise Human Identification

    J. Vasavi1, M. S. Abirami2,*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1349-1363, 2023, DOI:10.32604/iasc.2023.032604 - 05 January 2023

    Abstract In recent years, biometric sensors are applicable for identifying important individual information and accessing the control using various identifiers by including the characteristics like a fingerprint, palm print, iris recognition, and so on. However, the precise identification of human features is still physically challenging in humans during their lifetime resulting in a variance in their appearance or features. In response to these challenges, a novel Multimodal Biometric Feature Extraction (MBFE) model is proposed to extract the features from the noisy sensor data using a modified Ranking-based Deep Convolution Neural Network (RDCNN). The proposed MBFE model… More >

  • Open Access

    ARTICLE

    Cancellable Multi-Biometric Feature Veins Template Generation Based on SHA-3 Hashing

    Salwa M. Serag Eldin1,*, Ahmed Sedik2, Sultan S. Alshamrani3, Ahmed M. Ayoup4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 733-749, 2023, DOI:10.32604/cmc.2023.030789 - 22 September 2022

    Abstract In this paper, a novel cancellable biometrics technique called Multi-Biometric-Feature-Hashing (MBFH) is proposed. The MBFH strategy is utilized to actualize a single direction (non-invertibility) biometric shape. MBFH is a typical model security conspire that is distinguished in the utilization of this protection insurance framework in numerous sorts of biometric feature strategies (retina, palm print, Hand Dorsum, fingerprint). A more robust and accurate multilingual biological structure in expressing human loneliness requires a different format to record clients with inseparable comparisons from individual biographical sources. This may raise worries about their utilization and security when these spread More >

  • Open Access

    ARTICLE

    Secure and Anonymous Three-Factor Authentication Scheme for Remote Healthcare Systems

    Munayfah Alanazi*, Shadi Nashwan

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 703-725, 2022, DOI:10.32604/csse.2022.022962 - 04 January 2022

    Abstract Wireless medical sensor networks (WMSNs) play a significant role in increasing the availability of remote healthcare systems. The vital and physiological data of the patient can be collected using the WMSN via sensor nodes that are placed on his/her body and then transmitted remotely to a healthcare professional for proper diagnosis. The protection of the patient’s privacy and their data from unauthorized access is a major concern in such systems. Therefore, an authentication scheme with a high level of security is one of the most effective mechanisms by which to address these security concerns. Many… More >

  • Open Access

    ARTICLE

    Detecting Iris Liveness with Batch Normalized Convolutional Neural Network

    Min Long1,2,*, Yan Zeng1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 493-504, 2019, DOI:10.32604/cmc.2019.04378

    Abstract Aim to countermeasure the presentation attack for iris recognition system, an iris liveness detection scheme based on batch normalized convolutional neural network (BNCNN) is proposed to improve the reliability of the iris authentication system. The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris, including convolutional layer, batch-normalized (BN) layer, Relu layer, pooling layer and full connected layer. The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels, and then the iris features are extracted by BNCNN. With these features, the genuine iris and More >

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