Novel, comic-based approach to smartphone permission requests

This doctoral thesis investigates comics as a medium for presenting permission requests to users of smartphones and assessing how they can be used to support the users in making more informed decisions. Through three empirical studies, this thesis has generated insights into the creation of comic-based permission requests, the impact they have and what users would expect from them. In the first study, three co-design workshops were run where participants created their own comic requests, generating a series of design considerations for comic-based permission requests to better inform users. These considerations were used to design and develop the comic requests used in the subsequent studies to investigate if they supported users in making informed decisions in a balanced way. The comic-based permissions were evaluated by users in an online survey (Study 2) and in a WebApp (Study 3), to affirm the viability and the reliability of the considerations. The results of the evaluations suggest that comics are a viable medium to display more informative permission requests which help inform users and promote more informed decisions.James Watt Scholarshi

Smartphones: A Platform For Disaster Management

Bal, H.E. [Promotor]Kielmann, T. [Copromotor

Challenges and Outlook in Machine Learning-based Malware Detection for Android

Just like in traditional desktop computing, one of the major security issues in mobile computing lies in malicious software. Several recent studies have shown that Android, as today’s most widespread Operating System, is the target of most of the new families of malware. Manually analysing an Android application to determine whether it is malicious or not is a time- consuming process. Furthermore, because of the complexity of analysing an application, this task can only be conducted by highly-skilled—hence hard to come by—professionals. Researchers naturally sought to transfer this process from humans to computers to lower the cost of detecting malware. Machine-Learning techniques, looking at patterns amongst known malware and inferring models of what discriminates malware from goodware, have long been summoned to build malware detectors. The vast quantity of data involved in malware detection, added to the fact that we do not know a priori how to express in technical terms the difference between malware and goodware, indeed makes the malware detection question a seemingly textbook example of a possible Machine- Learning application. Despite the vast amount of literature published on the topic of detecting malware with machine- learning, malware detection is not a solved problem. In this Thesis, we investigate issues that affect performance evaluation and that thus may render current machine learning-based mal- ware detectors for Android hardly usable in practical settings, and we propose an approach to overcome those issues. While the experiments presented in this thesis all rely on feature-sets obtained through lightweight static analysis, several of our findings could apply equally to all Machine Learning-based malware detection approaches. In the first part of this thesis, background information on machine-learning and on malware detection is provided, and the related work is described. A snapshot of the malware landscape in Android application markets is then presented. The second part discusses three pitfalls hindering the evaluation of malware detectors. We show with extensive experiments how validation methodology, History-unaware dataset construction and the choice of a ground truth can heavily interfere with the performance results of malware detectors. In a third part, we present an practical approach to detect Android Malware in real-world settings. We then propose several research paths to get closer to our long term goal of building practical, dependable and predictable Android Malware detectors

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity