Workshop Mensch-Computer-Vernetzung Derzeitige Spam-Erkennung weist eklatante Mängel auf. Die Zunahme des Spam-Aufkommens erfordet neue Ansätze, um der Plage Herr zu werden. Der Vortrag erläutert, wie mit Hilfe des Satzes von Bayes die Spam-Erkennung deutlich verbessert werden kann.

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.

Low quality information such as spam and rumors is a nuisance to people and hinders them from consuming information that is pertinent to them or that they are looking for. As social networks like Facebook, Twitter and Google+ have become important communication platforms in people's daily lives, malicious users make them as major targets to pollute with low quality information, which we also call as Denial of Information (DoI) attacks. How to analyze and detect low quality information in social networks for preventing DoI attacks is the major research problem I will address in this dissertation. Although individual social networks are capable of filtering a significant amount of low quality information they receive, they usually require large amounts of resources (e.g, personnel) and incur a delay before detecting new types of low quality information. Also the evolution of various low quality information posts lots of challenges to defensive techniques. My work contains three major parts: 1). analytics and detection framework of low quality information, 2). evolutionary study of low quality information, and 3). detection approaches of low quality information. In part I, I proposed social spam analytics and detection framework SPADE across multiple social networks showing the efficiency and flexibility of cross-domain classification and associative classification. In part II, I performed a large-scale evolutionary study on web page spam and email spam over a long period of time. In part III, I designed three detection approaches used in detecting low quality information in social networks: click traffic analysis of short URL spam, behavior analysis of URL spam and information diffusion analysis of rumors in social networks. Our study shows promising results in analyzing and detecting low quality information in social networks.

Online social media, such as news websites and community question answering (CQA) portals, have made useful information accessible to more people. However, many of online comment areas and communities are flooded with fraudulent information. These messages come from a special group of online users, called online paid posters, or termed "Internet water army" in China, represents a new type of online job opportunities. Online paid posters get paid for posting comments or articles on different online communities and websites for hidden purpose, e.g., to influence the opinion of other people towards certain social events or business markets. Though an interesting strategy in business marketing, paid posters may create a significant negative effect on the online communities, since the information from paid posters is usually not trustworthy. We thoroughly investigate the behavioral pattern of online paid posters based on a real-world trace data from the social comments of a business conflict. We design and validate a new detection mechanism, including both non-semantic analysis and semantic analysis, to identify potential online paid posters. Using supervised and unsupervised approaches, our test results with real-world datasets show a very promising performance. / Graduate

Zugl.: Hagen, FernUniversity, Diss., 2006.

Universiẗat, Diss., 2006--Münster (Westfalen).

Zugl.: Hildesheim, Univ., Diss., 2009

Thesis (M.S.)--Michigan State University. Computer Science and Engineering, 2008. / Title from PDF t.p. (viewed on July 29, 2009) Includes bibliographical references (p. 45-47). Also issued in print.

Chemnitz, Techn. Univ., Studienarb., 2005.

Zugl.: Augsburg, Universiẗat, Diss., 2009.