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Distributed Rule Anomaly Detection in SDN-based IoT

The considerable growth of the number of networked devices in the world has led to the development of various and new programs in the field of IoT, which are often limited to the current network infrastructure, on the other hand, force the network administrator to implement complex network policies manually. Due to this congestion of equipment as well as the increasing complexity of traditional network configuration, Software-Defined Networks (SDNs) facilitate network management by separating the control and data layers and creating network rules. For these facilities, these networks appear to be a good infrastructure for IoT networks will enable network programming to develop new and more efficient services to meet real needs. In addition, the variety of IoT equipment can increase complex and inconsistent network rules in SDN-based switches, making network management difficult. Accordingly, in this paper, we will try to model the behavior of anomaly rules distributed in software-defined networks that have been created by different apps in the Internet of Things. It can identify their relationship with other rules in the network and avoid registering them.