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  • 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 to increase significantly. In 2016,… 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

    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 out designs are subverted as… More >

  • Open Access

    ARTICLE

    An Improved Biometric Fuzzy Signature with Timestamp of Blockchain Technology for Electrical Equipment Maintenance

    Rao Fu1,*, Liming Wang2, Xuesong Huo2, Pei Pei2, Haitao Jiang3, Zhongxing Fu4

    Energy Engineering, Vol.119, No.6, pp. 2621-2636, 2022, DOI:10.32604/ee.2022.020873

    Abstract The power infrastructure of the power system is massive in size and dispersed throughout the system. Therefore, how to protect the information security in the operation and maintenance of power equipment is a difficult problem. This paper proposes an improved time-stamped blockchain technology biometric fuzzy feature for electrical equipment maintenance. Compared with previous blockchain transactions, the time-stamped fuzzy biometric signature proposed in this paper overcomes the difficulty that the key is easy to be stolen by hackers and can protect the security of information during operation and maintenance. Finally, the effectiveness of the proposed method is verified by experiments. More >

  • Open Access

    ARTICLE

    A Novel Fusion System Based on Iris and Ear Biometrics for E-exams

    S. A. Shaban*, Hosnia M. M. Ahmed, D. L. Elsheweikh

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3295-3315, 2023, DOI:10.32604/iasc.2023.030237

    Abstract With the rapid spread of the coronavirus epidemic all over the world, educational and other institutions are heading towards digitization. In the era of digitization, identifying educational e-platform users using ear and iris based multimodal biometric systems constitutes an urgent and interesting research topic to preserve enterprise security, particularly with wearing a face mask as a precaution against the new coronavirus epidemic. This study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations (E-exams) during the COVID-19 pandemic. The proposed system comprises four steps. The first step is… More >

  • Open Access

    ARTICLE

    Optical Ciphering Scheme for Cancellable Speaker Identification System

    Walid El-Shafai1,2, Marwa A. Elsayed1, Mohsen A. Rashwan3, Moawad I. Dessouky1, Adel S. El-Fishawy1, Naglaa F. Soliman4, Amel A. Alhussan5,*, Fathi E. Abd El-Samie1

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 563-578, 2023, DOI:10.32604/csse.2023.024375

    Abstract Most current security and authentication systems are based on personal biometrics. The security problem is a major issue in the field of biometric systems. This is due to the use in databases of the original biometrics. Then biometrics will forever be lost if these databases are attacked. Protecting privacy is the most important goal of cancelable biometrics. In order to protect privacy, therefore, cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification databases. One methodology to achieve non-invertibility is the employment of non-invertible transforms. This… More >

  • Open Access

    ARTICLE

    Face Templates Encryption Technique Based on Random Projection and Deep Learning

    Mayada Tarek1,2,*

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2049-2063, 2023, DOI:10.32604/csse.2023.027139

    Abstract Cancellable biometrics is the solution for the trade-off between two concepts: Biometrics for Security and Security for Biometrics. The cancelable template is stored in the authentication system’s database rather than the original biometric data. In case of the database is compromised, it is easy for the template to be canceled and regenerated from the same biometric data. Recoverability of the cancelable template comes from the diversity of the cancelable transformation parameters (cancelable key). Therefore, the cancelable key must be secret to be used in the system authentication process as a second authentication factor in conjunction with the biometric data. The… More >

  • Open Access

    ARTICLE

    Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

    Harbi Al-Mahafzah1, Tamer AbuKhalil1, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5703-5715, 2022, DOI:10.32604/cmc.2022.030399

    Abstract Biometric verification has become essential to authenticate the individuals in public and private places. Among several biometrics, iris has peculiar features and its working mechanism is complex in nature. The recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition models. With this motivation, the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System (CKHDTL-BIRS). The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric verification. To achieve this, CKHDTL-BIRS model initially performs Median Filtering (MF)-based preprocessing and segmentation for… More >

  • Open Access

    ARTICLE

    Unconstrained Hand Dorsal Veins Image Database and Recognition System

    Mustafa M. Al Rifaee1,*, Mohammad M. Abdallah1, Mosa I. Salah2, Ayman M. Abdalla1

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5063-5073, 2022, DOI:10.32604/cmc.2022.030033

    Abstract Hand veins can be used effectively in biometric recognition since they are internal organs that, in contrast to fingerprints, are robust under external environment effects such as dirt and paper cuts. Moreover, they form a complex rich shape that is unique, even in identical twins, and allows a high degree of freedom. However, most currently employed hand-based biometric systems rely on hand-touch devices to capture images with the desired quality. Since the start of the COVID-19 pandemic, most hand-based biometric systems have become undesirable due to their possible impact on the spread of the pandemic. Consequently, new contactless hand-based biometric… More >

  • Open Access

    ARTICLE

    An Optimised Defensive Technique to Recognize Adversarial Iris Images Using Curvelet Transform

    K. Meenakshi1,*, G. Maragatham2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 627-643, 2023, DOI:10.32604/iasc.2023.026961

    Abstract Deep Learning is one of the most popular computer science techniques, with applications in natural language processing, image processing, pattern identification, and various other fields. Despite the success of these deep learning algorithms in multiple scenarios, such as spam detection, malware detection, object detection and tracking, face recognition, and automatic driving, these algorithms and their associated training data are rather vulnerable to numerous security threats. These threats ultimately result in significant performance degradation. Moreover, the supervised based learning models are affected by manipulated data known as adversarial examples, which are images with a particular level of noise that is invisible… 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 current time, with functions of… More >

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