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System and method for identifying phishing cyber-attacks through deep machine learning via a convolutional neural network (CNN) engine

机译:通过卷积神经网络(CNN)引擎通过深度机器学习识别网络钓鱼网络攻击的系统和方法

摘要

The presently disclosed subject matter includes a system for the detection of phishing cyber-attacks based on an application of deep machine learning techniques including the implementation of a deep convolutional neural network to determine whether a web element associated with a uniform resource locator is part of a phishing cyber-attack. The system produces a notification indicative of the phishing cyber-attack when a positive match between the uniform resource locator and the phishing cyber-attack is determined. The convolutional neural network is retrained at periodic time intervals with new datasets retrieved by an automated dataset collector and thus, improves the detection of zero-days cyber-attacks.
机译:当前公开的主题包括一种基于深度机器学习技术的应用程序的网络钓鱼网络攻击检测系统,该系统包括实现深度卷积神经网络以确定与统一资源定位器关联的网络元素是否是网络钓鱼攻击的一部分。网络钓鱼攻击。当确定统一资源定位符和网络钓鱼网络攻击之间的肯定匹配时,系统会生成指示网络钓鱼网络攻击的通知。卷积神经网络使用自动数据集收集器检索到的新数据集定期进行重新训练,从而改善了零日网络攻击的检测。

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