Web applications and APIs have become more popular every year, and security risks haveincreased. Along with more security risks and the large amount of sensitive informationshared on web applications today, the problem grows. I therefore wanted to explore morein security deficiencies to increase my own knowledge and others in the field. To do that,a web application was developed and a survey was made of what security threats existtoday and what solutions they have. Some of the solutions encountered during theinvestigation were then implemented and tested in the web application. The result showedsome general solutions such as validation, which was a solution to a number of threats.The investigation also showed that security is not black and white and that it is possibleto implement actions but attackers can still find ways to attack systems.

The implementation of a Course Management System into an educational institution oriented to students with learning disabilities such as ADHD,  represents a big challenge since these students experience persistent impairments in attention (or concentration) that impact negatively on their learning outcomes, engagement and motivation. It’s crucial to adapt and enhance these environments having in consideration the students’ special learning needs, in order to improve their user experience and engagement during their learning process. This thesis address the design and development of gamified layer that brings a current analog gamification practice into a Course Management System Environment, Google Classroom (GC). The prototype developed retrieves, transforms and shows the GC data in form of game elements such as points, badges, and progress bars, among others. After using the prototype during three weeks, the students showed an easy familiarization with the gamified layer of GC and an active participation and persistence during their course activities.

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The Swedish National Archives are in charge of the management of Common Specifications (CS). CS are genericmetadata specifications that provides structure and markup when transferring digital information betweeninformation systems and to electronic archives. As of now there is no CS for electronic healthcare records (EHR).Organizations around Sweden have developed their own specifications for transferring healthcare information. Inaddition to that, there are comprehensive international EHR metadata standards established. The Swedish NationalArchives have commissioned a study of EHR metadata specifications and standards to aid in the development of theCS.A Delphi study was conducted, including respondents from major archiving organizations in Sweden, to identifynecessary metadata categories when exchanging EHRs. The data was analyzed considering the international EHRmetadata standards HL7 CDA2 and CEN/ISO EN13606, as well as digital preservation metadata categories. Theresults were a set of metadata categories necessary to include in a CS. In addition, a subset of suggested mandatorymetadata categories is proposed and a list of implications for practice. Clinical codes, auditing, and separatingmetadata related to different contexts are a sample size of the implications.The results were evaluated in an interview with the Swedish National Archives, as well as Sydarkivera. Three criteriafor evaluating the results were proposed, being that the results had to consider a common terminology as well as bebased on a metadata standard and Swedish metadata specifications for EHRs. The interview revealed that the resultssatisfied these criterions, except for requiring a study on one additional user environment of EHRs.

Videoconferencing is one of the most common telepresence methods today and educational videos is rising in popularity among distance learners. Traditional videoconferencing is unable to convey gestures and mutual eye contact between participants. This study aim to propose a Virtual Reality telepresence solution using game engines. A literature study confirmed the effectiveness achieved in VR is comparable to the effectiveness in face-to-face meetings. The suggested solution implements whiteboard functionality from a real-life perspective, confirming it is possible to include new functionality and directly transfer old functionality to the VR system from the communication systems today. The system was evaluated based on the response time, packet loss, bandwidth, frame rate and through user tests. The evaluation shows it is possible to design a telepresence system with VR capable of passing the Turing Test for Telepresence. The participants of the user tests did not experience discomfort and they were positively inclined to the telepresence system. Though, discomfort may emerge if the VR character is used with a common office workstation. Future studies in this topic would involve modifications of the third person camera, making the head's rotation follow the direction of the camera view and implementing movable eye pupils on the VR character using the upcoming eye-tracking accessory.

The successful revival of three-dimensional (3D) cinema has generated a great deal of interest in 3D video. However, contemporary eyewear-assisted displaying technologies are not well suited for the less restricted scenarios outside movie theaters. The next generation of 3D displays, autostereoscopic multiview displays, overcome the restrictions of traditional stereoscopic 3D and can provide an important boost for 3D television (3DTV). Then again, such displays require scene depth information in order to reduce the amount of necessary input data. Acquiring this information is quite complex and challenging, thus restricting content creators and limiting the amount of available 3D video content. Nonetheless, without broad and innovative 3D television programs, even next-generation 3DTV will lack customer appeal. Therefore simplified 3D video content generation is essential for the medium's success. This dissertation surveys the advantages and limitations of contemporary 3D video acquisition. Based on these findings, a combination of dedicated depth sensors, so-called Time-of-Flight (ToF) cameras, and video cameras, is investigated with the aim of simplifying 3D video content generation. The concept of Time-of-Flight sensor fusion is analyzed in order to identify suitable courses of action for high quality 3D video acquisition. In order to overcome the main drawback of current Time-of-Flight technology, namely the high sensor noise and low spatial resolution, a weighted optimization approach for Time-of-Flight super-resolution is proposed. This approach incorporates video texture, measurement noise and temporal information for high quality 3D video acquisition from a single video plus Time-of-Flight camera combination. Objective evaluations show benefits with respect to state-of-the-art depth upsampling solutions. Subjective visual quality assessment confirms the objective results, with a significant increase in viewer preference by a factor of four. Furthermore, the presented super-resolution approach can be applied to other applications, such as depth video compression, providing bit rate savings of approximately 10 percent compared to competing depth upsampling solutions. The work presented in this dissertation has been published in two scientific journals and five peer-reviewed conference proceedings.  In conclusion, Time-of-Flight sensor fusion can help to simplify 3D video content generation, consequently supporting a larger variety of available content. Thus, this dissertation provides important inputs towards broad and innovative 3D video content, hopefully contributing to the future success of next-generation 3DTV.

Adoption of location-based services (LBS) was for a long time below expectations, and most of the studies attribute it to privacy concerns of users. However, many new LBS applications are currently among the most downloaded application for smartphones, particularly entertainment applications. Therefore, this research aims to find out whether privacy concerns still matter to users and to explore the role of the privacy in the adoption of LBS entertaining applications. The adopted methodology is qualitative research and data are collected through interviews and additional information from the smartphones ofparticipants. Ten individuals among university students at Linnaeus University in Sweden are selected for this research, and this sample choice is per their experience with two selected LBS entertaining applications, Pokémon Go and Tinder. As a result, six themes have been recognized to answer the research questions. Low privacy concerns about location information, especially in entertainment applications with negligible effect on adoption have been identified. However, author of this research suggests, that developers of LBS entertaining applications should care for retaining their credibility because it can have an impact on the adoption of their LBS services.

Idag är det vanligt att hantera, beskriva och konfigurera sin datainfrastruktur såsom processer, serverar och miljöer i maskinläsbara konfigurationsfiler istället för fysisk hårdvara eller interaktiva konfigureringsverktyg. Automatiserad datainfrastruktur blir mer och mer vanligt för att kunna fokusera mer på utveckling och samtidigt få ett stabilare system. Detta har gjort att antalet verktyg för automatisering av datainfrastruktur skjutit i höjden det senaste årtiondet. Lösningar för automatisering av olika typer av datainfrastrukturer har blivit mer komplexa och innehåller ofta många verktyg som interagerar med varandra. Det här kandidatarbetet jämför, väljer ut och sätter ihop existerande plattformar och verktyg och skapar ett privat moln som infrastruktur för utveckling. Detta för att effektivera livscykeln för en serverbaserad runtime-miljö. En jämförelse av molnplattformarna OpenStack, OpenNebula, CloudStack och Eucalyptus baserad på litteratur, lägger grunden för molnet. Molnplattformen kompletteras därefter med andra verktyg och lösningar för att fullborda livscykelautomatiseringen av runtime-miljöer. En prototyp av lösningen skapades för att analysera praktiska problem. Arbetet visar att en kombination av OpenStack, Docker, containerorkestrering samt konfigureringsverktyg är en lovande lösning. Lösningen skalar efter behov, automatiserar och hanterar verksamhetens konfigurationer för runtime-miljöer.

Fundamental properties of cloud computing such as resource sharing and on-demand self-servicing is driving a growing adoption of the cloud for hosting both legacy and new application services. A consequence of this growth is that the increasing scale and complexity of the underlying cloud infrastructure as well as the fluctuating service workloads is inducing performance incidents at a higher frequency than ever before with far-reaching impact on revenue, reliability, and reputation. Hence, effectively managing performance incidents with emphasis on timely detection, diagnosis and resolution has thus become a necessity rather than luxury. While other aspects of cloud management such as monitoring and resource management are experiencing greater automation, automated management of performance incidents remains a major concern. Given the volume of operational data produced by cloud datacenters and services, this thesis focus on how data analytics techniques can be used in the aspect of cloud performance management. In particular, this work investigates techniques and models for automated performance anomaly detection and prevention in cloud environments. To familiarize with developments in the research area, we present the outcome of an extensive survey of existing research contributions addressing various aspects of performance problem management in diverse systems domains. We discuss the design and evaluation of analytics models and algorithms for detecting performance anomalies in real-time behaviour of cloud datacenter resources and hosted services at different resolutions. We also discuss the design of a semi-supervised machine learning approach for mitigating performance degradation by actively driving quality of service from undesirable states to a desired target state via incremental capacity optimization. The research methods used in this thesis include experiments on real virtualized testbeds to evaluate aspects of proposed techniques while other aspects are evaluated using performance traces from real-world datacenters. Insights and outcomes from this thesis can be used by both cloud and service operators to enhance the automation of performance problem detection, diagnosis and resolution. They also have the potential to spur further research in the area while being applicable in related domains such as Internet of Things (IoT), industrial sensors as well as in edge and mobile clouds. / Grundläggande egenskaper för datormoln såsom resursdelning och självbetjäning driver ett växande nyttjande av molnet för internettjänster. En följd av denna tillväxt är att den underliggande molninfrastrukturens ökande storlek och komplexitet samt fluktuerade arbetsbelastning orsakar prestandaincidenter med högre frekvens än någonsin tidigare. En konsekvens av detta blir omfattande inverkan på intäkter, tillförlitlighet och rykte för de som äger tjänsterna. Det har därför blivit viktigt att snabbt och effektivt hantera prestandaincidenter med avseende på upptäckt, diagnos och korrigering. Även om andra aspekter av resurshantering för datormoln, som övervakning och resursallokering, på senare tid automatiserats i allt högre grad så är automatiserad hantering av prestandaincidenter fortfarande ett stort problem. Denna avhandling fokuserar på hur prestandahanteringen i molndatacenter kan förbättras genom användning av dataanalystekniker på de stora datamängder som produceras i de system som monitorerar prestanda hos datorresurser och tjänster. I synnerhet undersöks tekniker och modeller för automatisk upptäckt och förebyggande av prestandaanomalier i datormoln. För att kartlägga utvecklingen inom forskningsområdet presenterar vi resultatet av en omfattande undersökning av befintliga forskningsbidrag som behandlar olika aspekter av hantering av prestandaproblem inom i relevanta tillämpningsområden. Vi diskuterar design och utvärdering av analysmodeller och algoritmer för att upptäcka prestandaanomalier i realtid hos resurser och tjänster. Vi diskuterar också utformningen av ett maskininlärningsbaserat tillvägagångssätt för att mildra prestandaförluster genom att aktivt driva tjänsternas kvalitet från oönskade tillstånd till ett önskat målläge genom inkrementell kapacitetoptimering. Forskningsmetoderna som används i denna avhandling innefattar experiment på verkliga virtualiserade testmiljöer för att utvärdera aspekter av föreslagna tekniker medan andra aspekter utvärderas med hjälp av belastningsmönster från verkliga datacenter. Insikter och resultat från denna avhandling kan användas av både moln- och tjänsteoperatörer för att bättre automatisera detekteringen av prestandaproblem, inklusive dess diagnos och korrigering. Resultaten har också potential att uppmuntra vidare forskning inom området samtidigt som de är användbara inom relaterade områden som internet-av-saker, industriella sensorer, och storskaligt distribuerade moln eller telekomnätverk. / Cloud Control / eSSENCE

Global Navigation Satellite Systems (GNSS) have found wide adoption in various applications, be they military, civilian or commercial. The susceptibility of GNSS to radio-frequency interference can, thus, be very disruptive, even for emergency services, therefore threatening people's lives. An early prototype of a system providing relatively cheap widescale GNSS jamming detection, called J911, is explored in this thesis. J911 is smartphone-based crowdsourcing of GNSS observations, most interesting of which are carrier-to-noise-density ratio (<img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />) and Automatic Gain Control (AGC) voltage. To implement the prototype, an Android application to provide the measurements, a backend to parse and store the measurements, and a frontend to visualize the measurements were developed. In real-world use, the thesis argues, the J911 system would best be implemented over existing Enhanced 9-1-1 (E911) infrastructure, becoming a standardized part of the Public Switched Telephone Network (PSTN). The Android application, running on a smartphone, would periodically construct messages to be sent to the backend over an Internet connection. The messages would include: current location from all location providers available in Android OS, observed satellites from all supported constellations, the satellites' <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cfrac%7BC%7D%7BN_0%7D" />, and a timestamp. Once a message is received on the backend, the data would be extracted and stored in a database. The frontend would query the database and produce a map with the collected datapoints overlaid on top of it, whose color indicates received signal strength at that point. When a jammer gets close enough to a few smartphones, they will all be jammed, which is easily observed on the map. On top of that, if enough samples are gathered, a Power Difference of Arrival localization algorithm can be used to localize the jammer. The smartphones that the system was planned to be tested with did not support AGC level readings, therefore in order to obtain AGC levels over time, a few SiGe GN3S Samplers, which are radio-frequency frontends, were used. In eastern Idaho, United States, over three nights in July 2017, an exercise, named 2017 DHS JamX, was performed with the help of the US Department of Homeland Security. Sadly, the approval for the publication of the test results did not come in time to be included in this thesis.