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    Tytuł:
    Hybrid cryptography with a one-time stamp to secure contact tracing for COVID-19 infection
    Autorzy:
    El-Douh, Ahmed Abdel-Rahim
    Lu, Song Feng
    Elkouny, Abdelatif A.
    Amein, A.S.
    Powiązania:
    https://bibliotekanauki.pl/articles/2055157.pdf
    Data publikacji:
    2022
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    hybrid cryptography
    digital signature
    RSA
    AES
    asymmetric cryptography
    symmetric cryptography
    cybersecurity
    COVID-19
    kryptografia hybrydowa
    podpis elektroniczny
    kryptografia asymetryczna
    kryptografia symetryczna
    cyberbezpieczeństwo
    Opis:
    The COVID-19 pandemic changed the lives of millions of citizens worldwide in the manner they live and work to the so-called new norm in social standards. In addition to the extraordinary effects on society, the pandemic created a range of unique circumstances associated with cybercrime that also affected society and business. The anxiety due to the pandemic increased the probability of successful cyberattacks and as well as number and range. For public health officials and communities, location tracking is an essential component in the their efforts to combat the disease. The governments provide a lot of mobile apps to help health officials to trace the infected persons and contact them to aid and follow up on the health status, which requires an exchange of data in different forms. This paper presents the one-time stamp model as a new cryptography technique to secure different contact forms and protect the privacy of the infected person. The one-time stamp hybrid model consists of a combination of symmetric, asymmetric, and hashing cryptography in an entirely new way that is different from conventional and similar existing algorithms. Several experiments have been carried out to analyze and examine the proposed technique. Also, a comparison study has been made between our proposed technique and other state-of-the-art alternatives. Results show that the proposed one-time stamp model provides a high level of security for the encryption of sensitive data relative to other similar techniques with no extra computational cost besides faster processing time.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2022, 32, 1; 139--146
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Satellite Image Fusion Using a Hybrid Traditional and Deep Learning Method
    Autorzy:
    Hammad, Mahmoud M.
    Mahmoud, Tarek A.
    Amein, Ahmed Saleh
    Ghoniemy, Tarek S.
    Powiązania:
    https://bibliotekanauki.pl/articles/27314300.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    deep learning image fusion
    remote sensing image fusion
    remote sensing optical image
    pan-sharpening
    remote sensing image
    Opis:
    Due to growing demand for ground-truth in deep learning-based remote sensing satellite image fusion, numerous approaches have been presented. Of these approaches, Wald’s protocol is the most commonly used. In this paper, a new workflow is proposed consisting of two main parts. The first part targets obtaining the ground-truth images using the results of a pre-designed and well-tested hybrid traditional fusion method. This method combines the Gram–Schmidt and curvelet transform techniques to generate accurate and reliable fusion results. The second part focuses on the training of a proposed deep learning model using rich and informative data provided by the first stage to improve the fusion performance. The demonstrated deep learning model relies on a series of residual dense blocks to enhance network depth and facilitate the effective feature learning process. These blocks are designed to capture both low-level and high-level information, enabling the model to extract intricate details and meaningful features from the input data. The performance evaluation of the proposed model is carried out using seven metrics such as peak-signal-to-noise-ratio and quality without reference. The experimental results demonstrate that the proposed approach outperforms state-of-the-art methods in terms of image quality. It also exhibits the robustness and powerful nature of the proposed approach which has the potential to be applied to many remote sensing applications in agriculture, environmental monitoring, and change detection.
    Źródło:
    Geomatics and Environmental Engineering; 2023, 17, 5; 145--162
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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