Workshop "Netz- und Service-Infrastrukturen" Der Vortrag im Rahmen des Workshop "Netz- und Service-Infrastrukturen" stellt das Projekt Tripoli vor, zeigt Ziele und Prinzipien der erweiterten Emailumgebung (Empowered Email Environment, Tripple-E) für authentifizierten und zertifizierten Emailverkehr, Ablauf der Kommunikation und zu lösende Probleme auf.

Visual analytics (VA) solutions emerged in the past decade and tackled many problems in a variety of domains. The power of combining the abilities of human and machine creates fertile ground for new solutions to grow. However, the rise of these hybrid solutions complicates the process of evaluation. Unlike automated solutions, VA solutions behavior depends on the user who operates them. This creates a dimension of variability in measured performance. The existence of a human, on the other hand, allows researchers to borrow evaluation methods from domains, such as sociology. The challenge in these methods, however, lies in gathering and analyzing qualitative data to build valid evidence of usefulness.<div>This thesis tackles the challenge of evaluating the usefulness of VA solutions. We survey existing evaluation methods that have been used to assess VA solutions. We then analyze these methods in terms of validity and generalizability of their findings, as well as the feasibility of using them. Subsequently, we propose an evaluation framework which suggests evaluating VA solutions based on judgment analysis theory. The analysis provided by our framework is capable of quantitatively assessing the performance of a solution while providing a reason for the captured performance.<br></div><div>We have conducted multiple case studies in social spambot labeling domain to apply our theoretical discussion. We have developed a VA solution that tackles social spambot labeling problem, then use this solution to apply existing evaluation methods and showcase some of their limitations. Furthermore, we have used our solution to show the benefit yielded by our proposed evaluation framework.</div>

During natural disasters or crises, users on social media tend to easily believe contents of postings related to the events, and retweet the postings, hoping that the postings will be reached by many other users. Unfortunately, there are malicious users who understand the tendency and post misinformation such as spam and fake messages with expecting wider propagation. To resolve the problem, in this paper we conduct a case study of the 2013 Moore Tornado and Hurricane Sandy. Concretely, we (i) understand behaviors of these malicious users; (ii) analyze properties of spam, fake and legitimate messages; (iii) propose at and hierarchical classification approaches; and (iv) detect both fake and spam messages with even distinguishing between them. Our experimental results show that our proposed approaches identify spam and fake messages with 96.43% accuracy and 0.961 F-measure.

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Bitcoin scams cause billions of dollars worth of damage every year, targeting both large corporations as well as individuals. A commonly used method for these scams is spam emails. These emails all share the same intention of trying to trick people into sending Bit- coin to the address attached in the emails, which can be done using various methods like threats and social engineering. This thesis investigates Bitcoin spam emails and tries to dis- tinguish the characteristics of the successful ones. The study was conducted by collecting data on 250,000+ Bitcoin addresses from emails that have all been reported as spam to the Bitcoinabuse website. These addresses were analyzed using their number of transactions and final balance, which were extracted with a Python script using Blockchain’s public API. It was found that the successful Bitcoin spam emails only made up a tiny percentage of the entire data set. Looking at the most successful subset of spams, a few key aspects were found that distinguished them from the rest. The most successful spam emails were using blackmail techniques such as sextortion and ransomware to fool their victims. This method is believed to work so well because of the emotional response it invokes from the victims, which in many cases is enough for them to fold. In addition, luck seemed to play a rather big role for the scams to work. The emails had to reach the perfect target: a per- son that would fall for the trick, have money to send as well as the knowledge to buy and transfer Bitcoin. To increase the odds of finding these types of people, the scammers send emails in large volumes.

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Det ämne som undersöks i denna uppsats är attityden mot reklamutskick via SMS och e-post. Syftet är att undersöka vilka faktorer som bidrar till attityden och om åldern spelar in som en faktor och om attityden är densamma till reklamutskick via SMS som den är via e-post. En enkätundersökning har genomförts med 139 respondenter som låg till grund för den kvalitativa fokusgruppsundersökning som den största delen av resultatet bygger på. Enkäten har besvarats av individer runt om i Skåne som är i ålder 20 år och uppåt. Enkäten skapades för att kunna identifiera problem och perspektiv inom ämnet som sedan fokusgruppens diskussioner kunde bygga på. Fokusgruppen hade fem stycken medverkande och dessa individer representerade de olika åldersgrupper som enkäten omfattade. Vilket också resulterade i att det var olika åsikter som framkom och en diskussion kunde skapas utifrån olika perspektiv.Enkäten och transkriberingen från fokusgruppen har sedan resulterat i ett resultat som redovisar skillnader och likheter gällande acceptans och attityd mellan de olika kanalerna. Det visar också vilka faktorer som påverkade mottagandet av reklamutskicken via SMS och e-post. De slutsatser som kan dras från undersökningen är att attityden mot reklam via SMS och e-post är av negativ ton enligt fokusgruppen och enkätundersökningen. Om en positiv attityd ska kunna uppnås måste reklamutskicken vara bra utformade, skickas i rätt tid och ha en relevans till mottagaren och mottagarens livsstil. Man kan även dra slutsatsen att attityd inte kan kopplas ihop med ålder. Enkätundersökningen och fokusgruppen påvisar samma attityd och beteendemönster när det gäller SMS och e-post vid alla åldrar. / The topic that is examined in this paper is the attitude towards promotional messages through SMS and email. The aim is to examine the factors that contribute to the attitude, if age comes into play as a factor and if the attitude is the same for promotional messages via SMS as it is through email. An investigation has been conducted by means of a survey with 139 respondents that formed the basis of the qualitative focus group that the largest part of the result is based. Individuals around Skåne that are in the age 20 and up answered the questionnaire. The survey was designed to identify problems and perspectives that the focus group discussions could build on. The focus group had five participants and these individuals represented the different age groups that the survey encompassed. Which also resulted in different views that were aired and a discussion could be created with different perspectives involved.The inquiry and the transcript from the focus group demonstrate the differences and similarities regarding acceptance and attitude towards the different channels. They also show which factors affected the receipt of promotional mailings through SMS and email. The conclusions that can be drawn from the survey is that the attitude towards advertising through SMS and e-mail are with a negative tone according to the focus group and survey. That if a positive attitude is to be achieved, promotional mailings has to be well designed, have to be sent on time and have a relevance to the recipient and the recipient's lifestyle. One can also conclude that attitude cannot be connected with age. The survey and focus group are demonstrating the same attitude and behavior when it comes to SMS and email for all ages.

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Submitted by Milena Rubi (milenarubi@ufscar.br) on 2017-06-01T17:49:19Z No. of bitstreams: 1 SILVA_Tiago_2016.pdf: 13631569 bytes, checksum: 7774c3913aa556cc48c0669f686cd3b5 (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-06-01T17:49:26Z (GMT) No. of bitstreams: 1 SILVA_Tiago_2016.pdf: 13631569 bytes, checksum: 7774c3913aa556cc48c0669f686cd3b5 (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-06-01T17:49:32Z (GMT) No. of bitstreams: 1 SILVA_Tiago_2016.pdf: 13631569 bytes, checksum: 7774c3913aa556cc48c0669f686cd3b5 (MD5) / Made available in DSpace on 2017-06-01T17:49:38Z (GMT). No. of bitstreams: 1 SILVA_Tiago_2016.pdf: 13631569 bytes, checksum: 7774c3913aa556cc48c0669f686cd3b5 (MD5) Previous issue date: 2016-07-01 / Não recebi financiamento / The rapid popularization of smartphones has contributed to the growth of SMS usage as an alternative way of communication. The increasing number of users, along with the trust they inherently have in their devices, makes SMS messages a propitious environment for spammers. In fact, reports clearly indicate that volume of mobile phone spam is dramatically increasing year by year. SMS spam represents a challenging problem for traditional filtering methods nowadays, since such messages are usually fairly short and normally rife with slangs, idioms, symbols and acronyms that make even tokenization a difficult task. In this scenario, this thesis proposes and then evaluates a method to normalize and expand original short and messy SMS text messages in order to acquire better attributes and enhance the classification performance. The proposed text processing approach is based on lexicography and semantic dictionaries along with the state-of-the-art techniques for semantic analysis and context detection. This technique is used to normalize terms and create new attributes in order to change and expand original text samples aiming to alleviate factors that can degrade the algorithms performance, such as redundancies and inconsistencies. The approach was validated with a public, real and non-encoded dataset along with several established machine learning methods. The experiments were diligently designed to ensure statistically sound results which indicate that the proposed text processing techniques can in fact enhance SMS spam filtering. / A popularização dos smartphones contribuiu para o crescimento do uso de mensagens SMS como forma alternativa de comunicação. O crescente número de usuários, aliado à confiança que eles possuem nos seus dispositivos tornam as mensagem SMS um ambiente propício aos spammers. Relatórios recentes indicam que o volume de spam enviados via SMS está aumentando vertiginosamente nos últimos anos. SMS spam representa um problema desafiador para os métodos tradicionais de detecção de spam, uma vez que essas mensagens são curtas e geralmente repletas de gírias, símbolos, abreviações e emoticons, que torna até mesmo a tokenização uma tarefa difícil. Diante desse cenário, esta dissertação propõe e avalia um método para normalizar e expandir amostras curtas e ruidosas de mensagens SMS de forma a obter atributos mais representativos e, com isso, melhorar o desempenho geral na tarefa de classificação. O método proposto é baseado em dicionários lexicográficos e semânticos e utiliza técnicas modernas de análise semântica e detecção de contexto. Ele é empregado para normalizar os termos que compõem as mensagens e criar novos atributos para alterar e expandir as amostras originais de texto com o objetivo de mitigar fatores que podem degradar o desempenho dos métodos de classificação, tais como redundâncias e inconsistências. A proposta foi avaliada usando uma base de dados real, pública e não codificada, além de vários métodos consagrados de aprendizado de máquina. Os experimentos foram conduzidos para garantir resultados estatisticamente corretos e indicaram que o método proposto pode de fato melhorar a detecção de spam em SMS.

The purpose of this project is to design, build and implement a secure, payment-based email delivery system that provides privacy and reduces spam.