Android occupies a very large market share in the field of mobile devices, and quantities of applications are created everyday allowing users to easily use them. However, privacy leaks on Android terminals may result in serious losses to businesses and individuals. Current permission model cannot effectively prevent privacy data leakage. In this paper, we find a way to protect privacy data on Android terminals from the perspective of privacy information propagation by porting the concept of contextual integrity to the realm of privacy protection. We propose a computational model of contextual integrity suiting for Android platform and design a privacy protection system based on the model. The system consists of an online phase and offline phase; the main function of online phase is to computing the value of distribution norm and making privacy decisions, while the main function of offline phase is to create a classification model that can calculate the value of the appropriateness norm. Based on the 6 million permission requests records along with 2.3 million runtime contextual records collected by dynamic analysis, we build the system and verify its feasibility. Experiment shows that the accuracy of offline classifier reaches up to 0.94. The experiment of the overall system feasibility illustrates that 70% location data requests, 84% phone data requests and 46% storage requests etc., violate the contextual integrity.

Video traffic occupies a major part of current mobile traffic. The characteristics of video traffic are dominated by the behavior of the video application users. This paper uses a state transition diagram to analyze the behavior of video application users on smart phones. Video application users are divided into two categories; keyword search users and initial screen users. They take different first action in video viewing. The result of our analysis shows that the patience of video application users depends on whether they have a specific purpose when they launch a video application or not. Mobile network operators can improve the QoE of video application users by utilizing the results of this study.

This paper presents a system for automatic generation of dancing animation that is synchronized with a piece of music by re-using motion capture data. Basically, the dancing motion is synthesized according to the rhythm and intensity features of music. For this purpose, we propose a novel meta motion graph structure to embed the necessary features including both rhythm and intensity, which is constructed on the motion capture database beforehand. In this paper, we consider two scenarios for non-streaming music and streaming music, where global search and local search are required respectively. In the case of the former, once a piece of music is input, the efficient dynamic programming algorithm can be employed to globally search a best path in the meta motion graph, where an objective function is properly designed by measuring the quality of beat synchronization, intensity matching, and motion smoothness. In the case of the latter, the input music is stored in a buffer in a streaming mode, then an efficient search method is presented for a certain amount of music data (called a segment) in the buffer with the same objective function, resulting in a segment-based search approach. For streaming applications, we define an additional property in the above meta motion graph to deal with the unpredictable future music, which guarantees that there is some motion to match the unknown remaining music. A user study with totally 60 subjects demonstrates that our system outperforms the stat-of-the-art techniques in both scenarios. Furthermore, our system improves the synthesis speed greatly (maximal speedup is more than 500 times), which is essential for mobile applications. We have implemented our system on commercially available smart phones and confirmed that it works well on these mobile phones.

Next generation hand-held devices must provide seamless connectivity while obeying stringent power and size constrains. In this paper we examine this issue from the point of view of the Network Interface (NI). We measure the power usage of two PDAs, the Apple Newton Messagepad and Sony Magic Link, and four NIs, the Metricom Ricochet Wireless Modem, the AT&T Wavelan operating at 915 MHz and 2.4 GHz, and the IBM Infrared Wireless LAN Adapter. These measurements clearly indicate that the power drained by the network interface constitutes a large fraction of the total power used by the PDA. We then examine two classes of optimizations that can be used to reduce network interface energy consumption on these divices: transport-level strategies and application-level strategies. Simulation experiments of transport-level strategies show that the dominant cost comes not from the number of packets sent or received by a particular transport protocol but the amount of time that the NI is in an active but idle state. Simulation experiments of application-level strategies that significant energy savings can be made with a minimum of user-visible latency.