Biblio

Using the methods of literature and interview, this paper analyzes the current situation of performance evaluation of volunteers in large-scale games based on mobile Internet, By analyzing the popularity of mobile Internet, the convenience of performance evaluation, the security and privacy of performance evaluation, this paper demonstrates the necessity of performance evaluation of volunteers in large-scale games based on mobile Internet, This paper puts forward the Countermeasures of performance evaluation of volunteers in large-scale games based on mobile Internet.

With the rapid development of the mobile Internet, Android has been the most popular mobile operating system. Due to the open nature of Android, c countless malicious applications are hidden in a large number of benign applications, which pose great threats to users. Most previous malware detection approaches mainly rely on features such as permissions, API calls, and opcode sequences. However, these approaches fail to capture structural semantics of applications. In this paper, we propose AMDroid that leverages function call graphs (FCGs) representing the behaviors of applications and applies graph kernels to automatically learn the structural semantics of applications from FCGs. We evaluate AMDroid on the Genome Project, and the experimental results show that AMDroid is effective to detect Android malware with 97.49% detection accuracy.

As the technological progress of mobile Internet, smartphone based on Android OS accounts for the vast majority of market share. The traditional encryption technology cannot resolve the dilemma in smartphone information leakage, and the Android-based authentication system in view of biometric recognition emerge to offer more reliable information assurance. In this paper, we summarize several biometrics providing their attributes. Furthermore, we also review the algorithmic framework and performance index acting on authentication techniques. Thus, typical identity authentication systems including their experimental results are concluded and analyzed in the survey. The article is written with an intention to provide an in-depth overview of Android-based biometric verification systems to the readers.

With the rapid development of mobile internet, mobile devices are requiring more complex authorization policy to ensure an secure access control on mobile data. However mobiles have limited resources (computing, storage, etc.) and are not suitable to execute complex operations. Cloud computing is an increasingly popular paradigm for accessing powerful computing resources. Intuitively we can solve that problem by moving the complex access control process to the cloud and implement a fine-grained access control relying on the powerful cloud. However the cloud computation may not be trusted, a crucial problem is how to verify the correctness of such computations. In this paper, we proposed a public verifiable cloud access control scheme based on Parno's public verifiable computation protocol. For the first time, we proposed the conception and concrete construction of verifiable cloud access control. Specifically, we firstly design a user private key revocable Key Policy Attribute Based Encryption (KP-ABE) scheme with non-monotonic access structure, which can be combined with the XACML policy perfectly. Secondly we convert the XACML policy into the access structure of KP-ABE. Finally we construct a security provable public verifiable cloud access control scheme based on the KP-ABE scheme we designed.

Cellular towers capture logs of mobile subscribers whenever their devices connect to the network. When the logs show data traffic at a cell tower generated by a device, it reveals that this device is close to the tower. The logs can then be used to trace the locations of mobile subscribers for different applications, such as studying customer behaviour, improving location-based services, or helping urban planning. However, the logs often suffer from an oscillation phenomenon. Oscillations may happen when a device, even when not moving, does not only connect to the nearest cell tower, but is instead unpredictably switching between multiple cell towers because of random noise, load balancing, or simply dynamic changes in signal strength. Detecting and removing oscillations are a challenge when analyzing location data collected from the cellular network. In this paper, we propose an algorithm called SOL (Stable, Oscillation, Leap periods) aimed at discovering and reducing oscillations in the collected logs. We apply our algorithm on real datasets which contain about 18.9\textasciitildeTB of traffic logs generated by more than 3\textasciitildemillion mobile subscribers covering about 21000 cell towers and collected during 27\textasciitildedays from both GSM and UMTS networks in northern China. Experimental results demonstrate the ability and effectiveness of SOL to reduce oscillations in cellular network logs.