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Efficient Harmful Email Identification Using NeuralNetwork

机译:使用神经网络的有效有害电子邮件识别

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摘要

Phishing is a form of online fraud that aims to steal a user’s sensitive information such as online banking passwords or credit card numbers. In this paper, we present a technique to quickly detect suspicious email using Neural Network Pruning approach. The goal is to determine whether the email is suspicious or legitimate. A Multilayer feedforward neural network with Pruning Strategy is used for Feature Extraction and extracted features are used for identifying email as phishing email. Pruning Strategy extracts important features which are playing a key role in identifying phishing mail which looks similar to a legitimate one. To verify the feasibility of the proposed approach experimental evaluation has been performed using a dataset composed of phishing emails along with legitimate emails. The experimental results are satisfactory in terms of false positives and false negatives. The results of conducted test indicated good identification rate with very short processing time.
机译:网络钓鱼是一种在线欺诈手段,旨在窃取用户的敏感信息,例如在线银行密码或信用卡号。在本文中,我们提出了一种使用神经网络修剪方法快速检测可疑电子邮件的技术。目的是确定电子邮件是可疑的还是合法的。具有修剪策略的多层前馈神经网络用于特征提取,提取的特征用于将电子邮件识别为网络钓鱼电子邮件。修剪策略提取重要功能,这些功能在识别网络钓鱼邮件中起着至关重要的作用,这些邮件看起来类似于合法邮件。为了验证所提出方法的可行性,已经使用网络钓鱼电子邮件以及合法电子邮件组成的数据集进行了实验评估。就假阳性和假阴性而言,实验结果令人满意。进行的测试结果表明识别率很高,处理时间很短。

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