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    ARTICLE

    Alpha Fusion Adversarial Attack Analysis Using Deep Learning

    Mohibullah Khan1, Ata Ullah1, Isra Naz2, Sajjad Haider1, Nz Jhanji3,*, Mohammad Shorfuzzaman4, Mehedi Masud4

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 461-473, 2023, DOI:10.32604/csse.2023.029642 - 20 January 2023

    Abstract The deep learning model encompasses a powerful learning ability that integrates the feature extraction, and classification method to improve accuracy. Convolutional Neural Networks (CNN) perform well in machine learning and image processing tasks like segmentation, classification, detection, identification, etc. The CNN models are still sensitive to noise and attack. The smallest change in training images as in an adversarial attack can greatly decrease the accuracy of the CNN model. This paper presents an alpha fusion attack analysis and generates defense against adversarial attacks. The proposed work is divided into three phases: firstly, an MLSTM-based CNN More >

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