The nature of response to a successful cyberattack on any part of the smart grid is currently reactive. At any given time, the operators and security analysts at the utility command and control centers lack a complete picture of the grid’s security factors such as vulnerabilities, threats and attack vectors. Most of their valuable time goes towards releasing patches and adhering to the North American Electric Reliability Commission (NERC) Critical Infrastructure Protection (CIP) guidelines. In such an environment, the attackers are not only successful at breaking the system but also slip away before any countermeasure can be evoked by the defenders. The proposed project aims to bridge this gap by designing and developing an intelligent visualization, backed by three modules: Data (to develop contextual, processed data describing the situation of the grid), Classification (to classify processed data as erroneous, malicious, anomalous and correct data based on different rationales), and Action (to use the classified data and individual beliefs and experience as inputs to determine the best course of action to fulfill the intended objectives). Together, the three modules improve the situation awareness for the operators who can now make well-informed decisions in a timely manner, thereby making the whole process more proactive. The results from this research will be validated and then can be integrated with the corporate information systems of utilities. For more information about the project, please click here(