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  • Open Access

    ARTICLE

    X-MalNet: A CNN-Based Malware Detection Model with Visual and Structural Interpretability

    Kirubavathi Ganapathiyappan1, Heba G. Mohamed2, Abhishek Yadav1, Guru Akshya Chinnaswamy1, Ateeq Ur Rehman3,*, Habib Hamam4,5,6,7

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-18, 2026, DOI:10.32604/cmc.2025.069951 - 09 December 2025

    Abstract The escalating complexity of modern malware continues to undermine the effectiveness of traditional signature-based detection techniques, which are often unable to adapt to rapidly evolving attack patterns. To address these challenges, this study proposes X-MalNet, a lightweight Convolutional Neural Network (CNN) framework designed for static malware classification through image-based representations of binary executables. By converting malware binaries into grayscale images, the model extracts distinctive structural and texture-level features that signify malicious intent, thereby eliminating the dependence on manual feature engineering or dynamic behavioral analysis. Built upon a modified AlexNet architecture, X-MalNet employs transfer learning to… More >

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  • Open Access

    REVIEW

    Computing Challenges of UAV Networks: A Comprehensive Survey

    Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Xianxuan Lin4,*, Farman Ali5,*, Ahmad Ali AlZubi6

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1999-2051, 2024, DOI:10.32604/cmc.2024.056183 - 18 November 2024

    Abstract Devices and networks constantly upgrade, leading to rapid technological evolution. Three-dimensional (3D) point cloud transmission plays a crucial role in aerial computing terminology, facilitating information exchange. Various network types, including sensor networks and 5G mobile networks, support this transmission. Notably, Flying Ad hoc Networks (FANETs) utilize Unmanned Aerial Vehicles (UAVs) as nodes, operating in a 3D environment with Six Degrees of Freedom (6DoF). This study comprehensively surveys UAV networks, focusing on models for Light Detection and Ranging (LiDAR) 3D point cloud compression/transmission. Key topics covered include autonomous navigation, challenges in video streaming infrastructure, motivations for More >

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