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    ARTICLE

    A Convolution-Based System for Malicious URLs Detection

    Chaochao Luo1, Shen Su2, *, Yanbin Sun2, Qingji Tan3, Meng Han4, Zhihong Tian2, *

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 399-411, 2020, DOI:10.32604/cmc.2020.06507

    Abstract Since the web service is essential in daily lives, cyber security becomes more and more important in this digital world. Malicious Uniform Resource Locator (URL) is a common and serious threat to cybersecurity. It hosts unsolicited content and lure unsuspecting users to become victim of scams, such as theft of private information, monetary loss, and malware installation. Thus, it is imperative to detect such threats. However, traditional approaches for malicious URLs detection that based on the blacklists are easy to be bypassed and lack the ability to detect newly generated malicious URLs. In this paper, we propose a novel malicious… More >

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