Efficient Location Privacy In Mobile Applications

Location awareness is an essential part of today\u27s mobile devices. It is a well-established technology that offers significant benefits to mobile users. While location awareness has triggered the exponential growth of mobile computing, it has also introduced new privacy threats due to frequent location disclosures. Movement patterns could be used to identify individuals and also leak sensitive information about them, such as health condition, lifestyle, political/religious affiliations, etc. In this dissertation we address location privacy in the context of mobile applications. First we look into location privacy in the context of Dynamic Spectrum Access (DSA) technology. DSA is a promising framework for mitigating the spectrum shortage caused by fixed spectrum allocation policies. In particular, DSA allows license-exempt users to access the licensed spectrum bands when not in use by their respective owners. Here, we focus on the database-driven DSA model, where mobile users issue location-based queries to a white-space database in order to identify idle channels in their area. We present a number of efficient protocols that allow users to retrieve channel availability information from the white-space database while maintaining their location secret. In the second part of the dissertation we look into location privacy in the context of location-aware mobile advertising. Location-aware mobile advertising is expanding very rapidly and is forecast to grow much faster than any other industry in the digital era. Unfortunately, with the rise and expansion of online behavioral advertising, consumers have grown very skeptical of the vast amount of data that is extracted and mined from advertisers today. As a result, the consensus has shifted towards stricter privacy requirements. Clearly, there exists an innate conflict between privacy and advertisement, yet existing advertising practices rely heavily on non-disclosure agreements and policy enforcement rather than computational privacy guarantees. In the second half of this dissertation, we present a novel privacy-preserving location-aware mobile advertisement framework that is built with privacy in mind from the ground up. The framework consists of several methods which ease the tension that exists between privacy and advertising by guaranteeing, through cryptographic constructions, that (i) mobile users receive advertisements relative to their location and interests in a privacy-preserving manner, and (ii) the advertisement network can only compute aggregate statistics of ad impressions and click-through-rates. Through extensive experimentation, we show that our methods are efficient in terms of both computational and communication cost, especially at the client side

Developing Data Extraction and Dynamic Data Visualization (Styling) Modules for Web GIS Risk Assessment System (WGRAS)

Interactive web-GIS tools play an important role in determining disaster risk assessment which ultimately result in reduction of unexpected damages, cost and saves millions of lives. Disaster management practitioners largely benefited information at their disposal about location where possible incidents are eminent, anticipate the impact and project possible outcomes to help mitigate and organize proper response. It is also important to note that, accurate and timely information is critical for coherent coordination in response to disasters. All the above can be achieved through proper data collection combined with computer assisted modelling, analysis, production and timely dissemination of spatial information. This Master’s thesis aims to extend features of Web GIS for Risk Assessment (WGRAS) project conducted at the Department of Physical Geography and Ecosystem Science at Lund University. The work includes development of tools for geospatial data acquisition and extraction from freely available external open non-commercial sources and dynamic, user-oriented map Visualization allowing user-defined symbolization and coloring resulting flexible visual portrayal of geospatial data in the web environment. In this regard, solutions are driven based upon open source, open data and implementation strictly complies with open web standard protocols and web services. As a result, WGRAS is furnished with easy and user driven raw geo-spatial data extracts for an area of interest from OpenStreetMap (OSM). Thus, data is automatically stored for later use for different spatial modelling and analysis. The second most important contribution of this thesis is the feature developed to solve visualization of geographic information through a map server where maps are generated with a pre-defined style that limits user’s visual needs. Visualization module enables dynamic definition of style (symbolization and coloring) data which assist non-GIS expert to produce instant and meaningful presentation of maps to the end user. Overall, the work in this practical thesis adds value to disaster management and analysis in terms of easy provision of data and enabling clear dissection of disaster prone areas using effective visualization mechanism.Interactive web-GIS tools play an important role in determining disaster risk assessment which ultimately result in reduction of unexpected damages, cost and saves millions of lives. Disaster management practitioners largely benefited information at their disposal about location where possible incidents are eminent, anticipate the impact and project possible outcomes to help mitigate and organized response. It is also important to note that, accurate and timely information is critical for coherent coordination in response to disasters. This can be achieved through proper data collection combined with computer assisted modelling, analysis, production and timely dissemination of spatial information. This Master’s thesis aims to extend features of Web GIS for Risk Assessment (WGRAS) project conducted at the Department of Physical Geography and Ecosystem Science at Lund University. Modules are developed to enable easy integration of geospatial data extraction from freely available sources which are open to use and non-commercial. Implementation is facilitated with intuitive user interface which allows extracts for an area by location name(s) or area defined by two latitude and two longitude values. The other major contribution of the study focuses on visualization of geographic information in the web environment. Currently, map servers use pre-defined styling mechanism which virtually doesn’t satisfy user’s visual needs. This module enable dynamic and user-oriented map visualization allowing non-GIS experts to define (symbolization and colouring) and produce instant and meaningful presentation of maps to the end user. As recommendation, visualization of geographic data in the web environment should further be examined, especially the map servers in use should integrate powerful and meaningful dynamic styling on top existing pre-defined style. In conclusion, this thesis adds value for disaster management and analysis in terms of easy provision of geographic data and enabling clear dissection of disaster prone areas using effective visualization mechanism

Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade

Obstacles to wearable computing

In the year 2021, wearable technology could look beautiful and feel magical, but instead is exemplified by a plain wristband that looks suspiciously like a prison monitor. How can we make wearable technology that respects our privacy, enhances our daily lives, integrates with our other connected devices without leashing us to a smartphone, and visually expresses who we are? This study uses a novel method of participatory design fiction (PDFi) to understand potential users of everyday wearable technology through storytelling. I recruited participants from the general public and gave them a five-point prompt to create a design fiction (DF), which inspired the user-centred design of an everyday connected wearable device. The participants each received a technology probe to wear in the wild for a year. They then updated their DFs as a way to reflect on the implications of the technology. For the purposes of privacy, augmenting device functionality through interoperability, and integration into an Internet of Things (IoT) ecosystem, I used the Hub-of-All-Things personal data store to provide the software infrastructure. By listening to their stories, we can elicit design concepts directly from the users, to help us create wearable IoT devices that put the wearer at the centre of the design process, and are satisfying both functionally and emotionally.The Alan Turing Institute Doctoral Scheme, University of Cambridge Department of Computer Science and Technology, The Kenneth Hayter Memorial Fun

Geographic Information Systems and Science

Geographic information science (GISc) has established itself as a collaborative information-processing scheme that is increasing in popularity. Yet, this interdisciplinary and/or transdisciplinary system is still somewhat misunderstood. This book talks about some of the GISc domains encompassing students, researchers, and common users. Chapters focus on important aspects of GISc, keeping in mind the processing capability of GIS along with the mathematics and formulae involved in getting each solution. The book has one introductory and eight main chapters divided into five sections. The first section is more general and focuses on what GISc is and its relation to GIS and Geography, the second is about location analytics and modeling, the third on remote sensing data analysis, the fourth on big data and augmented reality, and, finally, the fifth looks over volunteered geographic information.info:eu-repo/semantics/publishedVersio

Earth Observation Open Science and Innovation

geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

Community memories for sustainable societies: The case of environmental noise

Sustainability is the main challenge faced by humanity today on global and local scales. Most environmental problems can be seen as the tragic overexploitation of a commons. In this dissertation we investigate how the latest developments within computer science and ICT can be applied to establish participatory, low-cost tools and practices that enable citizens to monitor, raise awareness about, and contribute to the sustainable management of the commons they rely on, and thereby protect or improve their quality of life. As a general approach we propose the use of community memories – as central data repositories and points of interaction for community members and other stakeholders – and the novel combination of participatory mobile sensing and social tagging – as a low-cost means to collect quantitative and qualitative data about the state of the commons and the health, well-being, behaviour and opinion of those that depend on it. Through applied, interdisciplinary research we develop a concrete solution for a specific, socially relevant problem, namely that of environmental noise – commonly referred to as noise pollution. Under the name NoiseTube we present an operational system that enables a participatory, low-cost approach to the assessment of environmental noise and its impact on citizens’ quality of life. This approach can be applied in the scope of citizen- or authority-led initiatives. The NoiseTube system consists of a sensing application – which turns mobile phones into a sound level meters and allows users to comment on their experience via social tagging – and a community memory – which aggregates and processes data collected by participants anywhere. The system supports and has been tested and deployed at different levels of scale – personal, group and mass sensing. Since May 2009 NoiseTube has been used by hundreds, if not thousands, of people all around the world, allowing us to draw lessons regarding the feasibility of different deployment, collaboration and coordination scenarios for participatory sensing in general. While similar systems have been proposed ours is the completest and most widely used participatory noise mapping solution to date. Our validation experiments demonstrate that the accuracy of mobile phones as sound level meters can be brought to an acceptable level through calibration and statistical reasoning. Through coordinated NoiseTube campaigns with volunteering citizens we establish that participatory noise mapping is a suitable alternative for, or a valuable complement to, conventional methods applied by authorities

The codification of local knowledges through digital cartographic artefacts: A Case study of the Humanitarian OpenStreetMap Team in Dar es Salaam, Tanzania.

The Humanitarian OpenStreetMap Team, affectionately known as HOT, worked on mapping the city of Dar es Salaam between 2014 and 2020. The efforts of HOT were designed to not only build a map of the city that would ‘put people on the map’, but to also use these maps to aid in development and humanitarian interventions through one of Africa’s fastest growing cities, all while using participatory mapping practices. This thesis examines the extent to which HOT has been able to achieve the creation of a new map of Dar es Salaam, the influence this map had on development projects, and the degree to which the map was built using participatory methods. The research undertook a deep analysis of map completion and accuracy and used interviews to explore the interplay between technology and micro/macro politics around the mapping of Dar es Salaam. Findings suggest that HOT is still underdeveloped as an organization and lacks the maturity to create true participatory models of working. That many of their practices were exclusionary to the local population and that weak management structures and procedures allowed colonial and ‘outsider’ saviour complexes to grow within the organisation. The work concludes by noting that HOT has begun to change many of its practices since 2020 where this research ends

Spatial and Temporal Sentiment Analysis of Twitter data

The public have used Twitter world wide for expressing opinions. This study focuses on spatio-temporal variation of georeferenced Tweets’ sentiment polarity, with a view to understanding how opinions evolve on Twitter over space and time and across communities of users. More specifically, the question this study tested is whether sentiment polarity on Twitter exhibits specific time-location patterns. The aim of the study is to investigate the spatial and temporal distribution of georeferenced Twitter sentiment polarity within the area of 1 km buffer around the Curtin Bentley campus boundary in Perth, Western Australia. Tweets posted in campus were assigned into six spatial zones and four time zones. A sentiment analysis was then conducted for each zone using the sentiment analyser tool in the Starlight Visual Information System software. The Feature Manipulation Engine was employed to convert non-spatial files into spatial and temporal feature class. The spatial and temporal distribution of Twitter sentiment polarity patterns over space and time was mapped using Geographic Information Systems (GIS). Some interesting results were identified. For example, the highest percentage of positive Tweets occurred in the social science area, while science and engineering and dormitory areas had the highest percentage of negative postings. The number of negative Tweets increases in the library and science and engineering areas as the end of the semester approaches, reaching a peak around an exam period, while the percentage of negative Tweets drops at the end of the semester in the entertainment and sport and dormitory area. This study will provide some insights into understanding students and staff ’s sentiment variation on Twitter, which could be useful for university teaching and learning management