Search Results - "malicious JavaScript detection"

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  1. 1

    A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors by Ndichu, Samuel, Kim, Sangwook, Ozawa, Seiichi, Misu, Takeshi, Makishima, Kazuo

    ISSN: 1568-4946, 1872-9681
    Published: Elsevier B.V 01.11.2019
    Published in Applied soft computing (01.11.2019)
    “…Websites attract millions of visitors due to the convenience of services they offer, which provide for interesting targets for cyber attackers. Most of these…”
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    Journal Article
  2. 2

    JSContana: Malicious JavaScript detection using adaptable context analysis and key feature extraction by Huang, Yunhua, Li, Tao, Zhang, Lijia, Li, Beibei, Liu, Xiaojie

    ISSN: 0167-4048, 1872-6208
    Published: Elsevier Ltd 01.05.2021
    Published in Computers & security (01.05.2021)
    “…JavaScript has played a crucial role in web development, making it a primary tool for hackers to launch assaults. Although malicious JavaScript detection…”
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    Journal Article
  3. 3

    Detecting malicious JavaScript code based on semantic analysis by Fang, Yong, Huang, Cheng, Su, Yu, Qiu, Yaoyao

    ISSN: 0167-4048, 1872-6208
    Published: Amsterdam Elsevier Ltd 01.06.2020
    Published in Computers & security (01.06.2020)
    “…Web development technology has undergone tremendous evolution, the creation of JavaScript has greatly enriched the interactive capabilities of the client…”
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    Journal Article
  4. 4

    Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation by Rozi, Muhammad Fakhrur, Ban, Tao, Ozawa, Seiichi, Yamada, Akira, Takahashi, Takeshi, Kim, Sangwook, Inoue, Daisuke

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2023
    Published in IEEE Access (2023)
    “…Malicious JavaScript code in web applications poses a significant threat as cyber attackers exploit it to perform various malicious activities. Detecting these…”
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    Journal Article
  5. 5

    An Approach for Malicious JavaScript Detection Using Adaptive Taylor Harris Hawks Optimization-Based Deep Convolutional Neural Network by Alex, Scaria, T, Dhiliphan Rajkumar

    ISSN: 1947-3532, 1947-3540
    Published: IGI Global 20.05.2022
    “…JavaScript has to become a pervasive web technology that facilitates interactive and dynamic Web sites. The extensive usage and the properties permit the…”
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    Journal Article
  6. 6

    Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences by Rozi, Muhammad Fakhrur, Kim, Sangwook, Ozawa, Seiichi

    ISSN: 2161-4407
    Published: IEEE 01.07.2020
    “…JavaScript is a dynamic computer programming language that has been used for various cyberattacks on client-side web applications. Malicious behaviors in…”
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    Conference Proceeding
  7. 7

    A Machine Learning Approach to Malicious JavaScript Detection using Fixed Length Vector Representation by Ndichu, Samuel, Ozawa, Seiichi, Misu, Takeshi, Okada, Kouichirou

    ISSN: 2161-4407
    Published: IEEE 01.07.2018
    “…To add more functionality and enhance usability of web applications, JavaScript (JS) is frequently used. Even with many advantages and usefulness of JS, an…”
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    Conference Proceeding