Mobile APP Usage Pattern Analysis Based On Network Access Data

With the smart phones and tablet PCs as the representative of the growing popularity of mobile devices, and the development of mobile network related software and hardware, the Internet has been changed from the traditional desktop Internet era into the mobile Internet era. With the advent of the mobile Internet era, many related behaviors or tools have undergone tremendous changes. In recent years, the unusually hot mobile apps are one of the results of the mobile Internet era.In the information age, a large number of APPs were released, while a large number of APPs were eliminated. For APP investors, a wrong investment or decision-making will result in huge losses. So we need to grasp the usage pattern of the APP, which can be used as an important dimension of the APP's popularity. Therefore, in this information age, we should be good at extracting the desired information from the big data, and make the right decisions based on the information. But, in order to extract the desired information from the massive network access data and obtain the APP mode of using, first of all, we need to get these characteristics of the APPs when they are downloaded or used, by generating traffic rules when the client and the server communicate.The purpose of this paper is to study how to automatically fetch the network traffic of APP's downloading operation and extract the traffic rules automatically. Firstly, the background of mobile APP is studied, and the main contents and research objectives are proposed. Secondly, this paper introduces some theoretical knowledge about Wireshark capturing packet and introduce the network traffic under the situation of APP's downloading and using, as well as the generation and follow-up of the traffic rules file based on the theoretical knowledge. Since there is only a small number of APPs, we can manually capture the APP network traffic. However, when the number of APPs is increasing, we need to consider the method of automation for saving manpower and time costs.Once again, the paper introduces how to achieve the automation of mobile APPs downloading operation, that is, the preparation of automated testing framework Robotium to simulate human gestures to achieve automation-download of APPs in the Android application market,including application store installation package re-signature, Android control positioning methods. And then use the Tcpdump command-line tool to achieve the traffic of APP downloading, and then write Python multi-threaded program with combining the above two to achieve the traffic capture automation of mobile APP downloading. Finally, we automate the extraction of traffic rules by writing Python programs to reduce the scope of human search for traffic rules and reduce the workload.At the end, the rules file is generated by downloading and using the APP. And then, we can get the welcome of the APP, and ultimately the usage pattern of APP by using the rules file in the massive network access data.