Tato práce pojednává o vytvoření mobilní aplikace zvažující kontext zařízení, která vybírá a doporučuje hudební skladby dle aktuálního stavu kontextu zařízení. Kontext je získáván na základě naměřených hodnot, které jsou získány z vestavěných senzorů mobilního zařízení a z ostatních systémových hodnot zařízení. Výběr konkrétní skladby je poté založen na výstupu modelu strojového učení, který klasifikuje kontext na základě aktuálních získaných dat a následně zvolí skladbu připadající k danému kontextu.

Handheld devices have a limited amount of screen real estate. If a handheld device could take advantage of larger screens, it would create a more powerful user interface and environment. As time progresses, Moore's law predicts that the computational power of handheld devices will increase dramatically in the future, promoting the interaction with a larger screen. Users can then use their peripheral vision to recognize spatial relationships between objects and solve problems more easily with this integrated system. In the spillable environment, the handheld device uses a DiamondTouch Table, a large, touch-sensitive horizontal table, to enhance the viewing environment. When the user moves the handheld device on the DiamondTouch, the orientation of the application changes accordingly. A user can let another person see the application by rotating the handheld device in that person's direction. A user could conveniently use this system in a public area. In a business meeting, a user can easily show documents and presentations to other users around the DiamondTouch table. In an academic setting, a tutor could easily explain a concept to a student. A user could effortlessly do all of this while having all of his/her information on the handheld device. A wide range of applications could be used in these types of settings.

Bluetooth is a technology that has been implemented in over 5 billion devices and therefore has a considerable impact. It is the dominant technology for shortrange wireless communication. Modern society relies heavily on information technology (IT), and this has introduced a significant threat to society and companies in the form of hackers whether they be state-sponsored, political activists, or part of organized crime. This has introduced the need for companies and organizations that strive to make devices more secure, as well as standards that can be used for evaluating how secure a device is. Common Criteria (CC) is an internationally recognized set of guidelines and standards that can be used for security evaluation. There is a growing demand for enhanced efficiency in the field of security evaluation, especially considering the move to agile methodologies in information and communication technology (ICT) product development. Historically, security evaluation has been tailored to each individual product. The current trends in the certification and global ICT evaluation industry indicate a move in the direction of a greater reliance on predefined test cases. In this thesis, I describe how I designed, developed, and evaluated a toolkit that automates the evaluation of Android devices concerning a selection of security requirements that concern Bluetooth from the Mobile Device Fundamentals Protection Profile in CC. This involved a literature study, examination of the Bluetooth Core Specification, software development, and evaluation of the toolkit. My results from evaluating the toolkit found that it only reports non-compliance with a security requirement if the target of evaluation (TOE) is non-compliant. Additionally, every time the toolkit reported compliance with a security requirement, manual evaluation verified that the TOE truly complied with the security requirement. Finally, during the development phase, I discovered a vulnerability that had not been discovered during manual evaluation. It has been confirmed by the developer to be a vulnerability and a patch is currently being developed. My evaluation indicates that the toolkit I have developed is reliable and that it could therefore be used in the security industry. By finding a vulnerability by using automation, I have shown that automation could potentially be a useful approach for vulnerability research. Similarly to fuzzing, automation can be used to expose a system to behavior that it does not expect and therefore potentially reveal vulnerabilities. / Bluetooth är en teknologi som har implementerats i över 5 miljarder enheter och har därför stor inverkan. Det är den dominerande teknologin för trädlös kommunikation med kort räckvidd. Det moderna samhället är starkt beroende av informationsteknologi (IT), och detta har introducerat ett betydande hot mot samhället och företag i form av hackare oavsett om de är statligt sponsrade, politiska aktivister, eller en del av organiserad brottslighet. Detta har introducerat ett behov av företag och organisationer som strävar efter att göra enheter säkrare, såväl som standarder som kan användas för att utvärdera hur säker en enhet är. Common Criteria (CC) är en internationellt erkänd uppsättning riktlinjer och standarder som kan användas för säkerhetsutvärdering. Det finns en växande efterfrågan på ökad effektivitet inom området för säkerhetsutvärdering, särskilt med tanke på övergången till agila metoder för produktutveckling inom information- och kommunikations-teknologi. Historiskt sett har säkerhetsutvärdering skräddarsytts för varje enskild produkt. De nuvarande trenderna i certifieringsindustrin och globala ICT-utvärderingsindustrin indikerar en förflyttning i riktning mot ett mer frekvent användande av fördefinierade testfall. I denna uppsats beskriver jag hur jag designade, utvecklade och utvärderade ett verktyg som automatiserar utvärderingen av Android-enheter gällande ett urval av säkerhetskrav som rör Bluetooth från Mobile Device Fundamentals Protection Profile i CC. Detta innebar en litteraturstudie, granskning av Bluetooth Core Specification, mjukvaruutveckling och utvärdering av verktyget. Mina resultat från utvärderingen av verktyget visade att den bara rapporterar bristande efterlevnad med ett säkerhetskrav om målet för utvärdering (TOE) inte efterlever säkerhetskravet i fråga. Dessutom, varje gång verktyget rapporterade överensstämmelse med ett säkerhetskrav, verifierade manuell utvärdering att TOE:n verkligen efterlevde säkerhetskravet i fråga. Slutligen, under utvecklingsfasen upptäckte jag en sårbarhet som inte upptäckts under manuell utvärdering. Sårbarhet har bekräftats av utvecklaren och en patch håller på att utvecklas. Min utvärdering visar att det verktyg som jag har utvecklat är tillförlitlig och att den därför skulle kunna användas i säkerhetsbranschen. Genom att hitta en sårbarhet genom automatisering har jag visat att automatisering skulle kunna vara en användbar metod för sårbarhetsforskning. På samma sätt som fuzzing kan automatisering används för att utsätta ett system för beteenden som det inte förväntar sig och därför potentiellt avslöja sårbarheter.

Recent accessibility drives and price wars between the major South African (SA) cell phone companies suggest that the landscape for the adoption of mobile learning (m-learning) at the Higher Education Institution (HEI) level may be changing. As such, there is a need to gauge the current mobile readiness of students for m-learning. Mobile technology readiness refers to the extent to which students have access to mobile devices (not only handsets), and can afford data bundles that meet or exceed the requirements of a base set of currently available m-learning applications (Naicker and Van der Merwe 2012). Mobile operational readiness refers to students’ awareness of, attitude towards, support and training that is required for m-learning. This study conducted an assessment of the technology and operational readiness of students at a SA HEI. An in-depth literature survey was undertaken to delineate technology and operational readiness of students for m-learning. For technology readiness, an investigation was conducted on m- learning applications that are currently available and the technology requirements of these mobile applications. This was undertaken to determine the extent that the current student mobile handset profile match these requirements. The literature review also included a search for mobile opeeratratiioonnaall ffaactorctorss ssuuchch aass ssttuuddeennttss’’ aawwaarenerenessss ooff aanndd aattttiittuuddee ttoowwaarrddss mm--lleaearrnininngg as well as m-learning support and training that students require. The philosophical underpinning of this study was based on Activity Theory. The strategy of inquiry employed was a case study approach. Data was collected from students at the Durban University of Technology, a resident based SA HEI. A mixed methods data collection strategy was employed. The researcher used a field survey questionnaire as the primary research instrument to assess mobile technology and operational readiness. Focus group interviews were used as a secondary data gathering tool to triangulate and strengthen the results. The results were presented using descriptive and inferential statistics and were analyzed using the lens of activity theory. In terms of technology readiness, despite a high level of ownership and reasonable compliance with application requirements, data costs remain prohibitive. In assessing operational readiness, despite a positive attitude, the majority of the students require awareness, ongoing support and training. Several recommendations based on the findings are offered. For example, one of the findings showed that mobile connectivity affordability was low amongst students and it is recommended that the HEI work around exorbitant connectivity costs by combining m-learning technologies to form meaningful m-learning approaches at a minimum v cost. Another finding showed low awareness of m-learning at the HEI. A recommendation advanced to combat this finding is for the HEI to encourage and support dialogue among key stakeholders. This study concludes that any m-learning endeavour to implement m-learning at this HEI is bound to fail as only a small percentage of students are aware of m-learning and can afford data bundles to implement m-learning in its true sense. As an implication of this study to other HEI’s, the researcher suggests that regular mobile readiness surveys be conducted. / Science and Technology Education / M. A. (Information Systems)

This master's project deals with location based systems and their application in information distribution. The work discuss kinds of getting actual location. Then it focuses on problems of developing applications and description of Microsoft technologies for mobile devices. Based on obtained theoretical information we present design, implementation and testing of our own location based system.

Recent accessibility drives and price wars between the major South African (SA) cell phone companies suggest that the landscape for the adoption of mobile learning (m-learning) at the Higher Education Institution (HEI) level may be changing. As such, there is a need to gauge the current mobile readiness of students for m-learning. Mobile technology readiness refers to the extent to which students have access to mobile devices (not only handsets), and can afford data bundles that meet or exceed the requirements of a base set of currently available m-learning applications (Naicker and Van der Merwe 2012). Mobile operational readiness refers to students’ awareness of, attitude towards, support and training that is required for m-learning. This study conducted an assessment of the technology and operational readiness of students at a SA HEI. An in-depth literature survey was undertaken to delineate technology and operational readiness of students for m-learning. For technology readiness, an investigation was conducted on m- learning applications that are currently available and the technology requirements of these mobile applications. This was undertaken to determine the extent that the current student mobile handset profile match these requirements. The literature review also included a search for mobile opeeratratiioonnaall ffaactorctorss ssuuchch aass ssttuuddeennttss’’ aawwaarenerenessss ooff aanndd aattttiittuuddee ttoowwaarrddss mm--lleaearrnininngg as well as m-learning support and training that students require. The philosophical underpinning of this study was based on Activity Theory. The strategy of inquiry employed was a case study approach. Data was collected from students at the Durban University of Technology, a resident based SA HEI. A mixed methods data collection strategy was employed. The researcher used a field survey questionnaire as the primary research instrument to assess mobile technology and operational readiness. Focus group interviews were used as a secondary data gathering tool to triangulate and strengthen the results. The results were presented using descriptive and inferential statistics and were analyzed using the lens of activity theory. In terms of technology readiness, despite a high level of ownership and reasonable compliance with application requirements, data costs remain prohibitive. In assessing operational readiness, despite a positive attitude, the majority of the students require awareness, ongoing support and training. Several recommendations based on the findings are offered. For example, one of the findings showed that mobile connectivity affordability was low amongst students and it is recommended that the HEI work around exorbitant connectivity costs by combining m-learning technologies to form meaningful m-learning approaches at a minimum cost. Another finding showed low awareness of m-learning at the HEI. A recommendation advanced to combat this finding is for the HEI to encourage and support dialogue among key stakeholders. This study concludes that any m-learning endeavour to implement m-learning at this HEI is bound to fail as only a small percentage of students are aware of m-learning and can afford data bundles to implement m-learning in its true sense. As an implication of this study to other HEI’s, the researcher suggests that regular mobile readiness surveys be conducted. / Science and Technology Education / M. Sc. (Information Systems)

Diese kumulative Dissertation untersucht die Rolle mobiler Geräte im Informationsverhalten junger Kinder aus verschiedenen Perspektiven. Einerseits wird erforscht, ob informationsbezogene Aktivitäten Teil der Nutzung mobiler Technologien durch junge Kinder sind. Andererseits wird untersucht, ob Aspekte des kindlichen Informationsverhaltens bei der Sichtweise von Eltern und Kinder auf die Nutzung von mobilen Geräten eine Rolle spielen. Die erste in dieser Arbeit vorgestellte Studie bietet einen explorativen Einblick in die Nutzung mobiler Geräte durch junge Kinder anhand von Interviews mit Eltern von Kindern im Alter von ein bis sechs Jahren. Basierend auf einer Sekundäranalyse der Interviewdaten wird im Rahmen der zweiten Studie erforscht, wie Eltern die Nutzung von Mobilgeräten durch ihre Kinder wahrnehmen und medienpädagogisch begleiten und diskutiert, wie dies das Informationsverhalten der Kinder beeinflussen könnte. Unter Anwendung eines Uses-and-Gratifications-Ansatzes wird in der dritten Studie untersucht, was Kundenrezensionen für ein Kinder-Tablet über die Nutzung des Geräts und die Erwartungen von Familien aussagen. In der vierten Studie wird anhand eines multimethodischen Ansatzes ein besonderer Fokus auf die Einbeziehung der kindlichen Perspektive gelegt und erforscht, wie Kinder im Alter von vier bis sechs Jahren mobile Geräte nutzen und ob Aspekte des kindlichen Informationsverhaltens eine Rolle bei der Sichtweise von Familien auf die Nutzung spielen. Insgesamt zeigen die Ergebnisse, dass mobile Geräte definitiv eine Rolle im Informationsverhalten von jungen Kindern einnehmen können, wobei ihr Potenzial für die Entdeckung von Informationen oftmals nicht im Vordergrund der Wahrnehmung durch Eltern und Kinder steht. Mit diesen Erkenntnissen leistet die Arbeit einen wichtigen Beitrag zur Adressierung bestehender Forschungslücken im Bereich des Informationsverhaltens junger Kinder im Allgemeinen sowie im spezifischen Kontext der Nutzung mobiler Geräte. / This cumulative doctoral thesis examines the role of mobile devices in young children's information behavior from different perspectives. On the one hand, it explores whether information-related activities are part of young children's use of mobile technologies. On the other hand, it investigates whether aspects of children's information behavior play a role in parents' and children's perceptions of mobile device use. The first study presented in this thesis gains exploratory insight into young children's use of mobile devices through interviews with parents of families with children aged one to six years. Based on a secondary analysis of the interview data, the second study examines how parents perceive and mediate young children's use of mobile devices and discusses how this might influence children's information behavior. By applying a uses and gratifications approach, the third study investigates what customer reviews for a tablet for children reveal about the use of this device and expectations of the families. Using a multi-method approach, the fourth study places a particular focus on the inclusion of children's perspectives and investigates how children aged four to six years use mobile devices and whether aspects related to children's information behavior play a role in families' perceptions of this use. Overall, the results show that mobile devices can clearly play a role in young children's information behavior, although their potential for children's information discovery is not always prominent in parents' and children's perceptions. With these findings, this work makes an important contribution to addressing existing research gaps regarding young children's information behavior in general as well as in the specific context of mobile device use.

At the beginning, the work describes DNS and SSL/TLS protocols, it mainly deals with communication between devices using these protocols. Then we'll talk about data preprocessing and data cleaning. Furthermore, the thesis deals with basic data mining techniques such as data classification, association rules, information retrieval, regression analysis and cluster analysis. The next chapter we can read something about how to identify mobile devices on the network. We will evaluate data sets that contain collected data from communication between the above mentioned protocols, which will be used in the practical part. After that, we finally get to the design of a system for analyzing network communication data. We will describe the libraries, which we used and the entire system implementation. We will perform a large number of experiments, which we will finally evaluate.