Graph-theoretic approach for security of Internet of Things
Farell Folly · 2017
The new trend of Internet is the connection of home devices to the rest of the world. This effect drastically increases the number of objects in the cloud, and hence, the amount of data that travels across the Internet. This research idea proposes a new approach for cyber threats mitigation in big size networks associated with high dynamicity, and an application to the Internet of Things. The model attempts to improve existing methods of threats detection by combining Data mining and Graph theory to detect anomalies in real-time and enable a given network with self-protection mechanisms against both known and new types of attacks. The results can be applied in social networks, sensors networks, communications networks or even in cyber physical networks. The objective is to find accurate metrics for evaluating the security risks associated with such networks and algorithms to determine the critical nodes, paths or sub-networks at risk.