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An Intelligent System for Phishing Attack Detection and Prevention

机译:一种智能系统,用于网络钓鱼攻击检测和预防

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Cyber security is a most important trepidation in the widespread adoption of internet technologies in the everyday activities of human being. Even though more sophisticated technologies emerged on the Internet, but different kinds of attacks and threats are also increasing day by day. Cyber attacks causes loss of customer confidence in adopting internet based applications. Phishing attack is one of the common vulnerabilities in the cyber space. Most of the anti-phishing solutions proposed so are focused only on a single issue and needs improvement. For malicious web page detection and prevention, an intelligent multi agent solution is proposed in this paper with the help of machine learning methods. The proposed approach detects both phishing sites and websites with malicious content. This multi-agent system contains four autonomous intelligent agents, which communicate with each other using the Extensible Messaging and Presence Protocol (XMPP) for decision-making. The first is a monitoring agent, second and third is for decision-making (using the machine-learning classifiers) and the fourth is for action-performing. The first agent is responsible for extracting URLs. It passes the extracted URLs to the second agent for feature extraction and classification. If any phishing is detected, the second agent communicates with the fourth agent and the site is blocked. Otherwise, the second agent communicates with the third agent for malicious script detection. If any malicious script is detected then the fourth agent blocks the entire web page. We have tested the performance and accuracy of the proposed method and obtained results ensures its efficiency.
机译:网络安全是在人类日常活动中广泛采用互联网技术的最重要的束缚。尽管互联网上出现了更复杂的技术,但不同种类的攻击和威胁也是日益增加的。网络攻击导致客户信心丧失采用基于互联网的应用程序。网络钓鱼攻击是网络空间中的常见漏洞之一。所提出的大多数防护解决方案仅在单一问题上集中并需要改善。对于恶意网页检测和预防,在本文的帮助下,在机器学习方法的帮助下提出了一个智能多代理解决方案。所提出的方法检测有恶意内容的网络钓鱼站点和网站。该多智能体系包含四个自主智能代理,它使用可扩展消息传递和存在协议(XMPP)相互通信,以进行决策。首先是监测代理,第二和第三是用于决策(使用机器学习分类器),第四个是用于执行执行。第一个代理负责提取URL。它将提取的URL传递给第二代理以进行特征提取和分类。如果检测到任何网络钓鱼,则第二种试剂与第四代理通信,并且该网站被阻止。否则,第二代理与第三代理通信进行恶意脚本检测。如果检测到任何恶意脚本,则第四个代理会阻止整个网页。我们已经测试了所提出的方法的性能和准确性,并获得的结果确保其效率。

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