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In this article, the authors have discussed about the connection between Internet of Things and growth of big data. They have also discussed short reference on the evolution, features, lifecycle, and implementation of Big Data from IoT over the cloud. Internet of Things represents a platform or environment that consists of enormous number of sensors and mediators interconnecting heterogeneous physical devices over the internet. IoT applications are available in many real-world areas such as smart city, smart workplace, smart home, smart transportation and various other ubiquitous computing areas. Using IoT applications generates tremendous amount of data for storage and management in the internet. With the time and research evolution integration of the IoT platforms and cloud comes in the market and IoT platforms data storage and management started shifting to the cloud from the internet connected physical systems for many real-world application areas. Meanwhile when this data becomes huge termed as Big Data. Handling of Big Data over the cloud develops many new areas of research and attention.

Mobile communication has various important issues such as congestion control, scarcity of radio spectrum, bandwidth utilization, and security. With increased number of threats in mobile devices, security has become the most important issue now-a-days. Security can be considered primarily at two levels; wireless transmission medium and mobile data level, where malicious applications execute their behavior by exploiting vulnerabilities present in mobile OS. The chapter also focuses on the latter one as these attacks can be easily performed by targeting vulnerabilities present in OS. The content is specifically on Android Operating System security as Android has become the largest installed base of mobile platform. This chapter specifies these vulnerabilities and focuses on malicious intentions of latest and sophisticated malware in detail. The chapter covers static and dynamic analysis tools as well as focuses on limitations of these methods for analyses. The results for malware samples with emulator detection capabilities show that these malware behaves more as benign samples.