Biblio

Reliable and secure grid operations become more and more challenging in context of increasing IT/OT convergence and decreasing dynamic margins in today's power systems. To ensure the correct operation of monitoring and control functions in control centres, an intelligent assessment of the different information sources is necessary to provide a robust data source in case of critical physical events as well as cyber-attacks. Within this paper, a holistic data stream assessment methodology is proposed using an expert knowledge based cyber-physical situational awareness for different steady and transient system states. This approach goes beyond existing techniques by combining high-resolution PMU data with SCADA information as well as Digital Twin and AI based anomaly detection functionalities.

One of the recent focuses in Cloud Computing networks is Software Defined Clouds (SDC), where the Software-Defined Networking (SDN) technology is combined with the traditional Cloud network. SDC is aimed to create an effective Cloud environment by extending the virtualization concept to all resources. In that, the control plane is decoupled from the data plane in a network device and controlled by the centralized controller using the OpenFlow Protocol (OFP). As the centralized controller performs all control functions in a network, it requires strong security. Already, Cloud Computing faces many security challenges. Most vulnerable attacks in SDC is Denial-of-Service (DoS) and Distributed DoS (DDoS) attacks. To overcome the DoS attacks, we propose a distributed Firewall with Intrusion Prevention System (IPS) for SDC. The proposed distributed security mechanism is investigated for two DoS attacks, ICMP and SYN flooding attacks for different network scenarios. From the simulation results and discussion, we showed that the distributed Firewall with IPS security detects and prevents the DoS attack effectively.