Deep learning-based browser record analysis research

Abstract

With the vigorous development of the Internet to combat criminal activities such as black and gray production, the problem of data classification is gradually being taken seriously. Therefore, by modeling and analyzing the browser history records that have been acquired, in which Chinese word separation in the field of neuro-linguistic programming (NLP) is used for word separation, feature extraction using a vocabulary table model, and classification processing by a neural network algorithm. Simulation experiments on browser history data through feature extraction and neural networks are conducted to train the accuracy of the model for analyzing browser history records and classifying the test data.