Cloud based intrusion detection architecture for smartphones

Smartphones are phones with advanced capabilities like those of personal computers (PCs). Smartphone technology is more and more becoming the predominant communication tool for people across the world. People use their smartphones to keep their contact data, to browse the internet, to exchange messages, to keep notes, carry their personal files and documents, etc. Users while browsing are also capable of shopping online, thus provoking a need to type their credit card numbers and security codes. As the smartphones are becoming widespread, it's also becoming a popular target for security threats and attack. Since smartphones use the same software architecture as in PCs, they are vulnerable to be exposed to similar threats such as in PCs. Recent news and articles indicate huge increase in malware and viruses for operating systems employed on smartphones (primarily Android and iOS). Major limitations of smartphone technology are its processing power and its scarce energy source since smartphones rely on battery usage. The smartphones have less storage and computational power to put into effect highly complex algorithms for intrusion detection and implementing signature based attack detection. Now in this paper, we propose a cloud based Intrusion Detection System for smartphones to overcome the issues of smartphone resource constraints and to detect any misbehavior or anomalous activity effectively

Profiling Power Consumption on Mobile Devices

The proliferation of mobile devices, and the migration of the information access paradigm to mobile platforms, motivate studies of power consumption behaviors with the purpose of increasing the device battery life. The aim of this work is to profile the power consumption of a Samsung Galaxy I7500 and a Samsung Nexus S, in order to understand how such feature has evolved over the years. We performed two experiments: the first one measures consumption for a set of usage scenarios, which represent common daily user activities, while the second one analyzes a context-aware application with a known source code. The first experiment shows that the most recent device in terms of OS and hardware components shows significantly lower consumption than the least recent one. The second experiment shows that the impact of different configurations of the same application causes a different power consumption behavior on both smartphones. Our results show that hardware improvements and energy-aware software applications greatly impact the energy efficiency of mobile device

Evaluating the performance of smartphones scanning for low energy beacons

Smartphones are now regularly used to scan for the presence of beacons. The information received by the scanner can be displayed or used to start other processes. It happens that smartphones fail to find beacons, although they are advertising. There are several reasons for that failure. A major one is the scanning behaviour of the smartphone. We designed and implemented ways of testing the performance of smartphones while they scan for Bluetooth Smart beacons or for low-power sensors. We used the tests to determine important tuning parameters. We also used the tests to compare a number of popular smartphones and verify the effect of parameter adjustments on their performances