The rapid development of the Internet has also brought opportunities for some illegal elements. Network attackers steal sensitive information from victims through phishing webpages to obtain economic benefits. Currently, the commonly used detection methods for phishing webpages, based on blacklist detection and webpage content feature detection, have the problems of being unable to detect newly emerging phishing webpages or requiring manual extraction of webpage features. Therefore, researchers have used Convolution Neural Network (CNN) to detect phishing webpages by automatically extracting URL features. However, its method has some limitations: (1) The memory is limited when the URL is transformed into the feature matrix, and the embedding vector of new words cannot be obtained or the effective information of sensitive words is lost; (2) the long-distance dependent feature of the URL cannot be obtained. In response to the above challenges, we proposes a phishing detection method based on CNN and Bi-directional Long Short-Term Memory (Bi-LSTM) based on existing work: based on sensitive word segmentation-- comprehensively using two existing URL segmentation methods before converting URL into eigenvector matrix; adding Bi-LSTM on the basis of convolutional neural network to obtain URL long-distance dependent features. Experimental results show that this method can achieve high accuracy, recall rate and F1 value.

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With the development of modern browsing, the convenience brought by rich browser features has also produced a large number of features, which are called browser fingerprints. This article surveys the latest research results on browser fingerprinting, hoping to provide a convenient navigation for newcomers to research or apply this technology in the future. This paper first briefly introduces the browser fingerprinting technology itself, then classifies the related research on browsers, and analyzes the development of different research directions of browser fingerprinting in detail. And through the analysis of the existing results, the problems faced by different research directions are pointed out. After that, this paper introduces the application of browser fingerprint technology in detail and discusses the application achievements and technical challenges of this technology. Next, this paper introduces the theoretical tools related to the research of browser fingerprinting technology and introduces the application of different theoretical tools and practical significance. Finally, the research achievements of browser fingerprint recognition are summarized, and the future development trend is pointed out.

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