Design and Implementation of the RSIL to LLVM IR Translator for Verification of the Intermediate Code on IoT Virtual Machine

Abstract

The phenomenon of sample impoverishment during particle filtering always contribute computation burden to the inertial-based mobile IPS systems. This is due to the factor of noise measurement and number of particle. Usually, the special strategies resampling algorithms was used. However, these algorithms just can fit in certain environment. This needs an adaptation of noise measurement and number of particle in a algorithm in order to make resampling with more intelligence, reliability and robust. In tbis paper, we will propose an adaptive special strategies resampling by adapting noise and particle measurement. These adaptation is used to determine the most suitable algorithm of special strategies resampling, that can be switched for resampling purpose. Finally, we illustrate our proposed solution our for indoor environment setup.

Privacy Rating of Mobile Applications Based on Crowdsourcing and Machine Learning

“…Through static analysis technology, it is easy to implement sensitive application permission analysis and analysis of usage permission schemes. In this paper, the decompilation process of the original mobile application Apk file is converted into an intermediate code by using the decompilation permission analysis tool Apktool (Son et al, 2017). On the one hand, we can directly obtain the application file with sensitive permissions of the mobile application.…”