Big Data Analytics for Detecting Host Misbehavior in Large Logs
Daniel Jorge Viegas Gonçalves, João Bota, Miguel Pupo Correia · 2015 IEEE Trustcom/BigDataSE/ISPA · 2015
The management of complex network infrastructures continues to be a difficult endeavor today. These infrastructures can contain a huge number of devices that may misbehave in unpredictable ways. Many of these devices keep logs that contain valuable information about the infrastructures' security, reliability, and performance. However, extracting information from that data is far from trivial. The paper presents a novel approach to assess the security of such an infrastructure using its logs, inspired on data from a real telecommunications network. We use machine learning and data mining techniques to analyze the data and semi-automatically discover misbehaving hosts, without having to instruct the system about how hosts misbehave.