MSNM-S: An Applied Network Monitoring Tool for Anomaly Detection in Complex Networks and Systems

Technology evolves quickly. Low cost and ready-to-connect devices are designed to provide new services and applications for a better people's daily life. Smart grids or smart healthcare systems are some examples of such applications all of them in the context of smart cities. In this all-connectivity scenario, some security issues arise since the larger is the number of connected devices the bigger is the surface attack dimension. This way, new solutions to monitor and detect security events are needed addressing new challenges coming from this scenario that are, among others, the number of devices to monitor, the huge amount of data to manage and the real time requirement to provide a quick security event detection and, consequently, quick attack reaction. In this work, the MSNM-Sensor is introduced, a practical and ready-to-use tool to monitor and detect security events able to manage this kind of environments. Although it is in its early development stages, experimental results based on the detection of well known attacks in hierarchical network systems proof its suitability to be applied in more complex scenarios like the ones found in smart cities or IoT ecosystems.