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首页> 外文期刊>Journal of Engineering & Applied Sciences >QRphish: An Automated QR Code Phishing Detection Approach
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QRphish: An Automated QR Code Phishing Detection Approach

机译:QRSHISH:自动QR码网络钓鱼检测方法

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摘要

Due to their advent and widespread demand, the smart mobiles have increased the use of Quick Response (QR) code technology. However, some phishers have started using certain features of the QR code to spread phishing frauds through smartphones. The QR code is a matrix barcode that allows easy interaction between mobile devices and websites or printed material by removing the burden of manually typing a URL or contact information. Phishers have started using the QR code for the phishing attacks. In this study we have proposed a new approach called "QRphish" which detects URL phishing on QR code. It uses the QR code-specific features and the URL features to detect whether the QR code content has a URL phishing or not. The QR code specific features used in this research use the QR code content and its characteristics like length, type and level of error correction. This method uses the machine learning classification technique. The proposed approach is evaluated by using benchmark dataset; the result shows a high accuracy in term of detecting URL phishing.
机译:由于他们的出现和广泛的需求,智能手机增加了快速响应(QR)代码技术的使用。但是,一些相比之下已经开始使用QR码的某些功能来传播通过智能手机的网络钓鱼欺诈。 QR码是一种矩阵条形码,可以通过去除手动键入URL或联系信息的负担来轻松地交互或通过打印的材料。 phishers已经开始使用QR码进行网络钓鱼攻击。在这项研究中,我们提出了一种称为“QRPH”的新方法,它检测QR码上的URL网络钓鱼。它使用QR码特定功能和URL功能来检测QR码内容是否具有URL网络钓鱼。本研究中使用的QR码特定功能使用QR码内容及其特征,如长度,类型和误差校正级别。该方法使用机器学习分类技术。通过使用基准数据集来评估所提出的方法;结果显示了检测URL网络训练的术语高精度。

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