A CleanRoom approach to bring your own apps

Today, on mobile devices such as smartphones and tablets, hundreds of thousands of software apps provide useful services to users. Users use these apps to search and browse the web, perform financial transactions, emailing, among other functions. Besides, these apps use cloud services which gives the users the flexibility to access them from anywhere and from any device. Because of the rich functionality of these apps and ease of use of mobile devices, users (employees) often want to use their devices and preferred apps at their workplace. However, these apps not only pose risk to user's private data but also to enterprise data, when users use them within an enterprise network. For one thing, these apps come from hundreds and thousands of different app publishers, where all of them may not be trustworthy. Second, apps often need user's private data such as location, contact list, photos among others and use remote cloud to carry out their operations. In the process apps may leak a user's private or enterprise confidential data to a third party. Current practices to prevent such leaks through user enabled app permissions fall short because often user does not understand these permissions. Besides, even if a company's "Bring Your Own Device" (BYOD) policies mitigate the risk of device compromise with enterprise-approved password policies, remote wipe capabilities, and OS security upgrade policies, the apps on those devices pose their own risks. This thesis presents CleanRoom, a new app platform that prevents apps from leaking the data entrusted to them. It does not rely on users to make good decisions about Privacy, and enables enterprises to allow its employees to use their own devices and bring their preferred apps to work.Computer Science

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Techniques for improving routing by exploiting user input and behavior

University of Minnesota Ph.D. dissertation. October 2014. Major: Computer Science. Advisor: Loren Terveen. 1 computer file (PDF); xiii, 106 pages.This dissertation explores innovative techniques for improving the route finding process. Instead of focusing on improving the algorithm itself, I aim to improve the other factors that make the route finding experience better: personalization, map data, and presentation. I do so by making extensive use of user input (both explicit and implicit) and crowdsourcing strategies. This research uses Cyclopath, a geowiki for cyclists in the Twin Cities, MN, as a case study for the various techniques explored.The first challenge is the lack of personalization in route finding algorithms. Aside from start and end points, algorithms usually know very little about users. However, user preferences can greatly affect their ideal routes. I studied the use of community-shared tags that allow users to specify preferences for those tags instead of doing so for each individual road segment, allowing them to easily express preference for a large number of roads with little effort. Correlation between individual road segment ratings and ratings deduced from tag preferences was evidence of the utility of this technique for making personalization easier.The second challenge is missing data. The best routing algorithm is only as good as the map data underneath it. Unfortunately, maps are often incomplete. They might not have updates on the latest construction, might be missing roads in rural areas or might not include detailed information such as lanes, trails, and even shortcuts. I present an HMM-based map matching algorithm that uses GPS traces recorded by users to generate potential new road segments. Tests within Cyclopath confirmed the abundance of missing roads and the ability of this algorithm to detect them.Finally, I look at the issue of unnatural presentation of routes. The way computers relay route directions is very different from humans, who use landmarks most of the time. However, gathering useful landmarks can be difficult and is often limited to points of interest. In this research, I tested methods for crowdsourcing different types of landmarks. I show that POIs are not sufficient to represent landmarks and that there is no objective truth regarding which landmarks are more useful to users

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described