Print Email Facebook Twitter Securing Social Media: A Network Structure Approach Title Securing Social Media: A Network Structure Approach Author Chiluka, N.J. Contributor Sips, H.J. (promotor) Faculty Electrical Engineering, Mathematics and Computer Science Department Software and Computer Technology Date 2013-06-04 Abstract Due to its democratized nature, online social media (OSM) attracts millions of users to publish and share their content with friends as well as a wider audience at little cost. Such a vast user base and a wealth of content, however, presents its own challenges. First, the amount of user-generated content being uploaded in their repositories makes it non-trivial for users to find relevant content. Second, the ease of creating an account and participating in OSM enables malicious users to spread and promote spam content while degrading the experience for normal users. Third, growing privacy concerns in OSM motivate users to move toward decentralized social networks which are still in a nascent stage. In this thesis, we propose a network structure approach to address these challenges in OSM. We build scalable and effective graph-based algorithms that recommend content personalized to each user. To tackle adversarial environments, we leverage the social network graph as well as negative feedback from normal users to limit the capability of knowledgeable attackers in multiple scenarios. Further, we highlight some of the practical limitations in existing efforts to build decentralized social networks, and explore new design point in this field which motivate practical designs for future social network-based distributed systems. Subject social networksybil defensetrust and distrust To reference this document use: https://doi.org/10.4233/uuid:9b2db13b-5948-4928-b3a4-c6df1ae1e9f1 Part of collection Institutional Repository Document type doctoral thesis Rights (c) 2013 Chiluka, N.J. Files PDF thesis_full.pdf 1.53 MB Close viewer /islandora/object/uuid:9b2db13b-5948-4928-b3a4-c6df1ae1e9f1/datastream/OBJ/view