Search Results - JavaScript malicious code

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  1. 1

    JACLNet:Application of adaptive code length network in JavaScript malicious code detection by Zhang, Zhining, Wan, Liang, Chu, Kun, Li, Shusheng, Wei, Haodong, Tang, Lu

    ISSN: 1932-6203, 1932-6203
    Published: United States Public Library of Science 14.12.2022
    Published in PloS one (14.12.2022)
    “…Currently, JavaScript malicious code detection methods are becoming more and more…”
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    Journal Article
  2. 2

    Detection of Obfuscated Malicious JavaScript Code by Alazab, Ammar, Khraisat, Ansam, Alazab, Moutaz, Singh, Sarabjot

    ISSN: 1999-5903, 1999-5903
    Published: Basel MDPI AG 01.08.2022
    Published in Future internet (01.08.2022)
    “…Websites on the Internet are becoming increasingly vulnerable to malicious JavaScript code because of its strong impact and dramatic effect…”
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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)
    “… However, attackers use the dynamics feature of JavaScript language to embed malicious code into web pages for the purpose of drive-by-download, redirection, etc…”
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    Journal Article
  4. 4

    Malicious JavaScript Code Detection Based on Hybrid Analysis by He, Xincheng, Xu, Lei, Cha, Chunliu

    ISSN: 2640-0715
    Published: IEEE 01.12.2018
    “… However, since the heavy use of obfuscation techniques, many methods no longer apply to malicious JavaScript code detection, and it has been a huge challenge to de-obfuscate obfuscated malicious Java…”
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    Conference Proceeding
  5. 5

    JStrong: Malicious JavaScript detection based on code semantic representation and graph neural network by Fang, Yong, Huang, Chaoyi, Zeng, Minchuan, Zhao, Zhiying, Huang, Cheng

    ISSN: 0167-4048, 1872-6208
    Published: Amsterdam Elsevier Ltd 01.07.2022
    Published in Computers & security (01.07.2022)
    “… However, the attacker uses the dynamic characteristics of the JavaScript language to embed malicious code into web pages to achieve the purpose of smuggling, redirection, and so on…”
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    Journal Article
  6. 6

    Analysis and Identification of Malicious JavaScript Code by Fraiwan, Mohammad, Al-Salman, Rami, Khasawneh, Natheer, Conrad, Stefan

    ISSN: 1939-3555, 1939-3547
    Published: Taylor & Francis Group 01.01.2012
    Published in Information security journal. (01.01.2012)
    “…Malicious JavaScript code has been actively and recently utilized as a vehicle for Web-based security attacks…”
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    Journal Article
  7. 7

    Detection Approach of Malicious JavaScript Code Based on deep learning by Zheng, Liyuan, Zhang, Dongcheng, Xie, Xin, Wang, Chen, Hou, Boyuan

    Published: IEEE 26.05.2023
    “…Traditional machine learning methods for detecting JavaScript malicious code have the problems of complex feature extraction process, extensive computation, and difficult detection due to malicious…”
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    Conference Proceeding
  8. 8

    MOJI: Character-level convolutional neural networks for Malicious Obfuscated JavaScript Inspection by Ishida, Minato, Kaneko, Naoshi, Sumi, Kazuhiko

    ISSN: 1568-4946, 1872-9681
    Published: Elsevier B.V 01.04.2023
    Published in Applied soft computing (01.04.2023)
    “… Many malicious JavaScript detection methods perform code abstraction and prior feature extraction to uncover the functionality hidden by obfuscation…”
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    Journal Article
  9. 9

    A Protection Mechanism against Malicious HTML and JavaScript Code in Vulnerable Web Applications by Chai, Chuansen, Zhao, Xu, Wang, Qingxian, Yan, Xuexiong, Liu, Shukai, Sun, Yajing

    ISSN: 1024-123X, 1563-5147
    Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2016
    Published in Mathematical problems in engineering (01.01.2016)
    “…The high-profile attacks of malicious HTML and JavaScript code have seen a dramatic increase in both awareness and exploitation in recent years…”
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    Journal Article
  10. 10

    The power of obfuscation techniques in malicious JavaScript code: A measurement study by Wei Xu, Fangfang Zhang, Sencun Zhu

    ISBN: 9781467348805, 1467348805
    Published: IEEE 01.10.2012
    “… Since most of the Internet users rely on anti-virus software to protect themselves from malicious JavaScript code, attackers exploit JavaScript obfuscation techniques to evade the detection of anti-virus software…”
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    Conference Proceeding
  11. 11

    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…”
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    Journal Article
  12. 12

    Filtering Malicious JavaScript Code with Doc2Vec on an Imbalanced Dataset by Mimura, Mamoru, Suga, Yuya

    Published: IEEE 01.08.2019
    “…Drive-by download attacks are one of main threats on the Internet. Several detection methods are to build run-time environments that allow JavaScript code to run and track its behavior while it runs…”
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    Conference Proceeding
  13. 13

    Detecting malicious JavaScript code in Mozilla by Hallaraker, O., Vigna, G.

    ISBN: 076952284X, 9780769522845
    Published: IEEE 2005
    “…). We propose an approach to solve this problem that is based on monitoring JavaScript code execution and comparing the execution to high-level policies, to detect malicious code behavior…”
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    Conference Proceeding
  14. 14

    自编码网络在JavaScript恶意代码检测中的应用研究 by 龙廷艳, 万良, 丁红卫

    ISSN: 1673-9418
    Published: 贵州大学 计算机软件与理论研究所,贵阳 550025 01.12.2019
    Published in 计算机科学与探索 (01.12.2019)
    “…TP391; 针对传统机器学习特征提取方法很难发掘JavaScript恶意代码深层次本质特征的问题,提出基于堆栈式稀疏降噪自编码网络(sSDAN)的JavaScript恶意代码检测方法.首先将JavaScript恶意代码进行数值化处理,然后在自编码网络的基础上加入稀疏性限制,同时加入一定概率分布的噪声进行染噪的学习训练…”
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    Journal Article
  15. 15

    Spider bird swarm algorithm with deep belief network for malicious JavaScript detection by Alex, Scaria, Dhiliphan Rajkumar, T

    ISSN: 0167-4048, 1872-6208
    Published: Amsterdam Elsevier Ltd 01.08.2021
    Published in Computers & security (01.08.2021)
    “… However, the flexibility of JavaScript made these applications more prone to attacks that induce malicious behaviors in the code…”
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    Journal Article
  16. 16

    A Survey on Current Malicious JavaScript Behavior of infected Web Content in Detection of Malicious Web pages by Nurulsafawati Wan Manan, Wan, Nizam Mohmad Kahar, Mohd, Mohd Ali, Noorlin

    ISSN: 1757-8981, 1757-899X
    Published: Bristol IOP Publishing 01.02.2020
    “… With the improvement of web technologies enable attackers to launch the web-based attacks and other malicious code easily without having prior expert knowledge…”
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    Journal Article
  17. 17

    PDF Malicious Indicators Extraction Technique Based on Improved Symbolic Execution by Song, Enzhou, Hu, Tao, Yi, Peng, Wang, Wenbo

    ISSN: 1002-137X
    Published: Chongqing Guojia Kexue Jishu Bu 01.07.2024
    Published in Ji suan ji ke xue (01.07.2024)
    “…The malicious PDF document is a common attack method used by APT organizations.Analyzing extracted indicators of embedded JavaScript code is an important means to determine the maliciousness…”
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    Journal Article
  18. 18

    JavaScript Malicious Codes Analysis Based on Naive Bayes Classification by Yongle Hao, Hongliang Liang, Daijie Zhang, Qian Zhao, Baojiang Cui

    Published: IEEE 01.11.2014
    “…Given the security threats of JavaScript malicious codes attacks in the Internet environment, this paper presents a method that uses the Naive Bayes classification to analyze JavaScript malicious codes…”
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    Conference Proceeding
  19. 19

    Behavior Analysis Usage with Behavior Tures Adoption for Malicious Code Detection on JAVASCRIPT Scenarios Example by Y. M. Tumanov, S.V. Gavrilyuk

    ISSN: 2074-7128, 2074-7136
    Published: Joint Stock Company "Experimental Scientific and Production Association SPELS 01.03.2010
    “…The article offers the method of malicious JavaScript code detection, based on behavior analysis…”
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    Journal Article
  20. 20

    AMA: Static Code Analysis of Web Page for the Detection of Malicious Scripts by Seshagiri, Prabhu, Vazhayil, Anu, Sriram, Padmamala

    ISSN: 1877-0509, 1877-0509
    Published: Elsevier B.V 2016
    Published in Procedia computer science (2016)
    “… To defend against obfuscated malicious JavaScript code, we propose a mostly…”
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    Journal Article