<p>It is very probable that VoIP will soon replace the ordinary telephone. Beside all advantages of the digital voice-connection it is linked to the danger of spam on the telephone. A lot of approaches have been developed to solve the problem of VoIP spam. Because some of these solutions are based on access to personal information of its users, a broad discussion about the best and most ethical approach has started.</p><p>This thesis analyzes the users’ point of view towards the VoIP spam problem and the extent of users’ willingness to offer private information in order to avoid VoIP spam. It presents results from a qualitative and a quantitative research as well as approaches for a most realistic- and most promising VoIP solution. These new approaches are based on the results of the research.</p><p>The main points of the results showed that users were not willing to offer private information to companies and that they were not willing to pay any amount of money for VoIP spam solutions. Users held governmental organisations and telephone operators responsible for finding a solution against VoIP spam.</p>

Bakgrund: Det konsumenter oftast inte är medvetna om vid deras Internetanvändning är att de iakttas av företag. Företagen samlar avsiktligt in personlig information och spårar vilka hemsidor och produkter eller tjänster de intresserat sig av genom så kallade webb-spårningssystem. I samma takt som tekniker så som webb-spårningssystem börjat användas har också etisk marknadsföring på Internet blivit ett diskuterat och aktuellt ämne. Etisk marknadsföring på Internet handlar om vad som uppfattas som accepterat beteende av konsumenterna och företag måste ta hänsyn till konsumentens etiska koder. Syfte: Syftet med studien är att undersöka konsumenters uppfattningar om webbspårningssystem utifrån etiska koder. Forskningsfråga: Vad är etiskt accepterat användande av webb-spårningssystem från konsumentens perspektiv? Metod: I studien har en kvalitativ forskningsstrategi samt semi-strukturerade intervjuer tillämpats. Slutsats: Slutsatsen i studien är att konsumenters uppfattningar om webb-spårningssystem inte alltid uppfyller konsumentens etiska koder. Konsumenter har generellt sätt en negativ uppfattning om webb-spårningssystem men uppfattningarna skiljer sig beroende på vilken situation som konsumenten påverkas av webb-spårningssystem. Konsumenter har enbart positiva uppfattningar om webb-spårningssystem när tekniken används så att konsumenten gynnas av den.

"Mitteilungen des URZ" 4/2003

Nutzerinformationen des Universitätsrechenzentrums

It is very probable that VoIP will soon replace the ordinary telephone. Beside all advantages of the digital voice-connection it is linked to the danger of spam on the telephone. A lot of approaches have been developed to solve the problem of VoIP spam. Because some of these solutions are based on access to personal information of its users, a broad discussion about the best and most ethical approach has started. This thesis analyzes the users’ point of view towards the VoIP spam problem and the extent of users’ willingness to offer private information in order to avoid VoIP spam. It presents results from a qualitative and a quantitative research as well as approaches for a most realistic- and most promising VoIP solution. These new approaches are based on the results of the research. The main points of the results showed that users were not willing to offer private information to companies and that they were not willing to pay any amount of money for VoIP spam solutions. Users held governmental organisations and telephone operators responsible for finding a solution against VoIP spam.

This diploma thesis deals with the issue of security risks and threats of social networks. The work includes basic information about the most popular online social networks such as Facebook, Twitter and Instagram. The work analyzes the development and use of the above mentioned networks. In addition, there are the risks and dangers of communicating on social networks and recommendations for safe use.

In the modern world, email communication defines itself as the most used technology for exchanging messages between users. It is based on three pillars which contribute to the popularity and stimulate its rapid growth. These pillars are represented by free availability, efficiency and intuitiveness during exchange of information. All of them constitute a significant advantage in the provision of communication services. On the other hand, the growing popularity of email technologies poses considerable security risks and transforms them into an universal tool for spreading unsolicited content. Potential attacks may be aimed at either a specific endpoints or whole computer infrastructures. Despite achieving high accuracy during spam filtering, traditional techniques do not often catch up to rapid growth and evolution of spam techniques. These approaches are affected by overfitting issues, converging into a poor local minimum, inefficiency in highdimensional data processing and have long-term maintainability issues. One of the main goals of this master's thesis is to develop and train deep neural networks using the latest machine learning techniques for successfully solving text-based spam classification problem belonging to the Natural Language Processing (NLP) domain. From a theoretical point of view, the master's thesis is focused on the e-mail communication area with an emphasis on spam filtering. Next parts of the thesis bring attention to the domain of machine learning and artificial neural networks, discuss principles of their operations and basic properties. The theoretical part also covers possible ways of applying described techniques to the area of text analysis and solving NLP. One of the key aspects of the study lies in a detailed comparison of current machine learning methods, their specifics and accuracy when applied to spam filtering. At the beginning of the practical part, focus will be placed on the e-mail dataset processing. This phase was divided into five stages with the motivation of maintaining key features of the raw data and increasing the final quality of the dataset. The created dataset was used for training, testing and validation of types of the chosen deep neural networks. Selected models ULMFiT, BERT and XLNet have been successfully implemented. The master's thesis includes a description of the final data adaptation, neural networks learning process, their testing and validation. In the end of the work, the implemented models are compared using a confusion matrix and possible improvements and concise conclusion are also outlined.

HBFG-ProjektMONARCH Version 1.2 Unerwuenschte Botschaften: E-Mail-Spams Cross-Zertifizierung DFN -- IN e.V. Campusnetzzugang in Hoersaelen StarOffice fuer Linux Freeware, Shareware und Public Domain (Softwarerecht) Weihnachtswuensche Coverage{10}: 22.12.2017

Mitteilungen des URZ 4/2002

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