| Abstract |
The Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) Cyber Security for Energy Delivery Systems (CSEDS) industry led program (DE-FOA-0000359) entitled 'Innovation for Increasing Cyber Security for Energy Delivery Systems (12CSEDS),' awarded a contract to Sypris Electronics LLC to develop a Cryptographic Key Management System for the smart grid (Scalable Key Management Solutions for Critical Infrastructure Protection). Oak Ridge National Laboratory (ORNL) and Sypris Electronics, LLC as a result of that award entered into a CRADA (NFE- 11-03562) between ORNL and Sypris Electronics, LLC. ORNL provided its Cyber Security Econometrics System (CSES) as a tool to be modified and used as a metric to address risks and vulnerabilities in the management of cryptographic keys within the Advanced Metering Infrastructure (AMI) domain of the electric sector. ORNL concentrated our analysis on the AMI domain of which the National Electric Sector Cyber security Organization Resource (NESCOR) Working Group 1 (WG1) has documented 29 failure scenarios. The computational infrastructure of this metric involves system stakeholders, security requirements, system components and security threats. To compute this metric, we estimated the stakes that each stakeholder associates with each security requirement, as well as stochastic matrices that represent the probability of a threat to cause a component failure and the probability of a component failure to cause a security requirement violation. We applied this model to estimate the security of the AMI, by leveraging the recently established National Institute of Standards and Technology Interagency Report (NISTIR) 7628 guidelines for smart grid security and the International Electrotechnical Commission (IEC) 63351, Part 9 to identify the life cycle for cryptographic key management, resulting in a vector that assigned to each stakeholder an estimate of their average loss in terms of dollars per day of system operation. To further address probabilities of threats, information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain from NESCOR WG1. From these five selected scenarios, we characterized them into three specific threat categories affecting confidentiality, integrity and availability (CIA). |
