期刊名称：International Journal of Early Childhood Special Education
电子版ISSN：1308-5581
出版年度：2022
卷号：14
期号：5
页码：1457-1459
DOI：10.9756/INTJECSE/V14I5.145
语种：English
出版社：International Journal of Early Childhood Special Education
摘要：Most people are familiar with phishing, where an attacker sends out a malicious email that pretends to be legitimate. Common phishing emails pretending to be notifications from trusted organizations (banks, Amazon, Netflix, etc.) that require the recipient to log into their account to fix the issue. By setting up a website that mimics the legitimate site, attackers can collect login credentials and other personal information.Utilization of cloud services is increasing, web application users are increasing, network architecture connecting devices running mobile operating systems is changing, and network technology is always expanding, creating new difficulties for cyber security. In order to fulfil the wants and issues of the users, network security methods, sensors, and protection schemes must also advance in order to counter emerging threats.Since they are ranked as the top dangers and the biggest difficulty for network and cyber security, we concentrate on preventing rising application layer cyber attacks in this article.The article's main contribution is its suggestion of using machine learning to predict the typical behaviour of applications and identify cyberattacks.The model consists of patterns that are obtained by applying graph-based segmentation technique and dynamic programming (in the form of Perl Compatible Regular Expressions (PCRE) regular expressions).The model is founded on data gathered from HTTP requests made by clients to web servers.We tested our approach using the CSIC 2010 HTTP Dataset, and the results were satisfactory.
关键词：Application layer;detection of cyberattacks;phishing emails;spear phishing
