Identification of Smartphone Applications by Encrypted Traffic Analysis

Abstract

The requirements of smartphone users have shifted from the quality of service (i.e., throughput) to the quality of experience. Also, the amount of encrypted traffic has increased to protect personal information. Therefore, to provide a quality mobile network experience for smartphone users, network operators need to identify applications from the encrypted traffic and control their traffic. In this paper, we propose a method of identifying applications running on a specific smartphone by analyzing only the time series patterns in IP traffic without inspecting the encrypted traffic. The proposed method estimates application flow with a two-level probabilistic state transition model and identifies applications on the basis of the statistics per estimated flow. Through experiments identifying applications running on a smartphone, we evaluated the estimation accuracy of proposed method.