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首页> 外文期刊>Programming and Computer Software >Improving Efficiency of Web Application Firewall to Detect Code Injection Attacks with Random Forest Method and Analysis Attributes HTTP Request
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Improving Efficiency of Web Application Firewall to Detect Code Injection Attacks with Random Forest Method and Analysis Attributes HTTP Request

机译：提高Web应用程序防火墙的效率，以检测随机林法和分析属性HTTP请求的代码注入攻击

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摘要

In the era of information technology, the use of computer technology for both work and personal use is growing rapidly with time. Unfortunately, with the increasing number and size of computer networks and systems, their vulnerability also increases. Protecting web applications of organizations is becoming increasingly relevant as most of the transactions are carried out over the Internet. Traditional security devices control attacks at the network level, but modern web attacks occur through the HTTP protocol at the application level. On the other hand, the attacks often come together. For example, a denial of service attack is used to hide code injection attacks. The system administrator spends a lot of time to keep the system running, but they may forget the code injection attacks. Therefore, the main task for system administrators is to detect network attacks at the application level using a web application firewall and apply effective algorithms in this firewall to train web application firewalls automatically for increasing his efficiency. The article introduces parameterization of the task for increasing the accuracy of query classification by the random forest method, thereby creating the basis for detecting attacks at the application level.
机译：在信息技术的时代，使用计算机技术对工作和个人使用的使用时间随着时间的推移而迅速增长。不幸的是，随着计算机网络和系统的数量和大小的越来越大，他们的漏洞也会增加。保护组织的Web应用正在变得越来越相关，因为大多数交易都在互联网上进行。传统安全设备控制网络级别的攻击，但现代Web攻击通过HTTP协议在应用程序级别进行。另一方面，攻击通常会走到一起。例如，拒绝服务攻击用于隐藏代码注入攻击。系统管理员花了很多时间来保持系统运行，但他们可能会忘记代码注入攻击。因此，系统管理员的主要任务是使用Web应用程序防火墙检测应用程序级别的网络攻击，并在此防火墙中应用有效算法以自动培训Web应用程序防火墙以提高他的效率。本文介绍了任务的参数化，用于提高随机森林方法的查询分类准确性，从而为检测应用程序级别的攻击创造基础。

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