Discouraging abusive behavior in privacy-preserving decentralized online social networks
Álvaro García Recuero · HAL (Le Centre pour la Communication Scientifique Directe) · 2017
The main goal of this thesis is to evaluate privacy-preserving protocols to detect abuse in future decentralised online social platforms or microblogging services, where often limited amount of metadata is available to perform data analytics. Taking into account such data minimization, we obtain acceptable results compared to techniques of machine learning that use all metadata available. We draw a series of conclusion and recommendations that will aid in the design and development of a privacy-preserving decentralised social network that discourages abusive behavior.