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    The era of advanced machine learning and deep learning algorithms for malware detection

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    Author
    Lytras, Miltiadis cc
    Kwok Tai Chui
    Patricia Ordóñez de Pablos
    Ryan Wen Liu
    Chien-wen Shen
    Subject
    Deep Learning
    Advanced Machine Learning
    Date
    January 2022
    
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    Abstract
    Software has been the essential element to computers in today's digital era. Unfortunately, it has experienced challenges from various types of malware, which are designed for sabotage, criminal money-making, and information theft. To protect the gadgets from malware, numerous malware detection algorithms have been proposed. In the olden days there were shallow learning algorithms, and in recent years there are deep learning algorithms. With the availability of big data for training of model and affordable and high-performance computing services, deep learning has demonstrated its superiority in many smart city applications, in terms of accuracy, error rate, etc. This chapter intends to conduct a systematic review on the latest development of deep learning algorithms for malware detection. Some future research directions are suggested for further exploration.
    Department
    Computer Science
    Publisher
    IGI Global
    Book title
    Advances in Malware and Data-Driven Network Security
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