Front-end Design Framework for Analytics of Risky Behaviour in Corporate Smartphones

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As mobile devices such as smartphones become increasingly ubiquitous and pervasive, such devices are subject to security threats and malicious intrusions. High risk user behaviour, loss of the mobile device, or an attack on the device by a third party can lead to leakage of sensitive information and damage to critical infrastructure, especially when such devices are used by corporate employees for both work-related and personal purposes. Mobile device behaviour analytics can be a powerful tool to capture, analyze and predict threats in order to detect and prevent intrusions on such devices. Much of the previous research has focused on user behavior analysis and extraction of traffic patterns from the perspective of cellular network providers, application developers and operating system vendors. It is this research gap that is addressed by this proposal. The objective of this proposal is to conduct a study on the first step in building a design framework for the analytics of risky user behavior in corporate smartphones. The research questions addressed in this proposal are the following: 1.What mobile device behavior analytics data can be collected from Android and iOS devices? 2.How can data be optimally captured in a lightweight application to send to an analytics engine? The project will make a detailed analysis of current techniques and technologies available for smartphone user analytics, investigate what types of data can be extracted from smartphone user behavior analytics, identify a shortlist of data that can be used as predictors for high risk, and make recommendations of mechanisms that could be used as viable solutions for the design of the front end analytics engine. This project addresses an important first step for the industry partner, namely, Nova Communications, towards the deployment and commercialization of a mobile device behaviour analytics engine.