Development of a typing behaviour recognition mechanism on Android

This paper proposes a biometric authentication system which use password based and behavioural traits (typing behaviours) authentication technology to establish user’s identity on a mobile phone. The proposed system can work on the latest smart phone platform. It uses mobile devices to capture user’s keystroke data and transmit it to web server. The authentication engine will establish if a user is genuine or fraudulent. In addition, a multiplier of the standard deviation “α” has been defined which aims to achieve the balance between security and usability. Experimental results indicate that the developed authentication system is highly reliable and very secure with an equal error rate is below 7.5%

Green multimedia: informing people of their carbon footprint through two simple sensors

In this work we discuss a new, but highly relevant, topic to the multimedia community; systems to inform individuals of their carbon footprint, which could ultimately effect change in community carbon footprint-related activities. The reduction of carbon emissions is now an important policy driver of many governments, and one of the major areas of focus is in reducing the energy demand from the consumers i.e. all of us individually. In terms of CO2 generated from energy consumption, there are three predominant factors, namely electricity usage, thermal related costs, and transport usage. Standard home electricity and heating sensors can be used to measure the former two aspects, and in this paper we evaluate a novel technique to estimate an individual's transport-related carbon emissions through the use of a simple wearable accelerometer. We investigate how providing this novel estimation of transport-related carbon emissions through an interactive web site and mobile phone app engages a set of users in becoming more aware of their carbon emissions. Our evaluations involve a group of 6 users collecting 25 million accelerometer readings and 12.5 million power readings vs. a control group of 16 users collecting 29.7 million power readings

Reliable online social network data collection

Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users’ behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.Postprin

Mining Mobile Youth Cultures

In this short paper we discuss our work on coresearch devices with a young coder community, which help investigate big social data collected by mobile phones. The development was accompanied by focus groups and interviews on privacy attitudes, and aims to explore how youth cultures are tracked in mobile phone data

Conceivable security risks and authentication techniques for smart devices

With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques

Developing digital interventions: a methodological guide.

Digital interventions are becoming an increasingly popular method of delivering healthcare as they enable and promote patient self-management. This paper provides a methodological guide to the processes involved in developing effective digital interventions, detailing how to plan and develop such interventions to avoid common pitfalls. It demonstrates the need for mixed qualitative and quantitative methods in order to develop digital interventions which are effective, feasible, and acceptable to users and stakeholders

The role of places and spaces in lifelog retrieval

Finding relevant interesting items when searching or browsing within a large multi-modal personal lifelog archive is a significant challenge. The use of contextual cues to filter the collection and aid in the determination of relevant content is often suggested as means to address such challenges. This work presents an exploration of the various locations, garnered through context logging, several participants engaged in during personal information access over a 15 month period. We investigate the implications of the varying data accessed across multiple locations for context-based retrieval from such collections. Our analysis highlights that a large number of spaces and places may be used for information access, but high volume of content is accessed in few