Framework for collecting social network events

Abstract

Online Social Networks became a relevant part of daily digital interactions for more than half a billion users around the world. The various personal information sharing practices that social network providers promote have led to their success as innovative social interaction platforms. At the same time, these practices have risen much critique and concerns with respect to privacy and security from different stakeholders. In fact, the massive use of online social networks has risen the attention of hackers and attackers that want to propagate malware and viruses for obtaining sensitive data. In this way, every social network user should be able to easily access, control and analyse the information he shares on his profile in order to efficiently detect any usage deviation. The possibility of detecting different sources of shared information in the same account lead us to design a system based not on information itself but on the timestamps associated to it. The proposed event collector framework can collect all posted information and store it in a relational database for further analysis. Using a friendly graphical interface, users can access all stored information in a comprehensible manner, according to the type of event, thus facilitating the analysis of the user behaviour. Since each event is stored with its corresponding timestamp, it is possible to perform an efficient analysis of all posted contents, compute statistics over collected data, infer/establish the so called "normal" or "typical" usage profile and, thus, be able to detect possible deviations that may correspond to a compromised user account.