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  • 标题:MALICIOUS URL CLASSIFICATION SYSTEM USING MULTI-LAYER PERCEPTRON TECHNIQUE
  • 本地全文:下载
  • 作者:MOHAMMAD FAZLI BAHARUDDIN ; TENGKU ADIL TENGKU IZHAR ; MOHD SHAMSUL MOHD SHOID
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2018
  • 卷号:96
  • 期号:19
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Currently web-based applications, such as online shopping, education and web based discussion forums are popular. The employments of these applications have successfully assist organizations to stay competitive. Nevertheless, most of website developers are using Content Management Systems (CMS) as a platform to build a website. CMS provides third party plug-in in which this services has lack of control. CMS is designed to enable non-technical user with less knowledge on computer programming, graphics imaging tools, or markup language like HTML to develop their own website. The drawbacks that were highlighted when using CMS are software and operating systems are patched for security threats. Due to lack of patching by the user, hackers can use unpatched CMS software to exploit vulnerabilities to enter the website or web based application. This is the evident of exposing web application to cyber security risks such as malicious Uniform Resource Locator (URL). Meanwhile, malicious URL is the URL of a website that attempts to do the illegal activities on the client side. Furthermore some malicious URL can embed the malicious scripts into the web pages and exploit the vulnerabilities when the user browses such websites. This study is a baseline of measuring the effectiveness of identifying Malicious URLs by using Multi-Layer Perceptron Technique. The identification of malicious URL will be beneficial to web developer to improve the security of web based application. It is then assisting the user or organizations to access the websites without hesitate and doubt. By providing the necessary result and outputs of the effectiveness, this information can be used either for future research of any machine learning techniques.
  • 关键词:Malicious URL Classification; Multi-Layer Perceptron; Content Management System; Web-based Application; Web Vulnerability
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