Analytics for Smart Grid Security and Resiliency

Abstract

The security and resiliency analysis of a smart grid needs to consider the target component(s), flexible attack model, and the integration among different smart grid components and attack properties. An exhaustive security analysis is not only expensive but also infeasible using testbeds. Formal analytics can play an important role toward comprehensive security analysis of the system, which can identify potential threats provably, that can further be verified on testbeds.Recent research studies have established the capability of formal models for analyzing security and resiliency of different components of a smart grid [1,19,[21][22][23][24][25]. The proactive identification of security threats is performed by developing formal security verification techniques that discover cyber and physical security threats on different components of smart grids, including AMI, SCADA, and EMS. Dynamic security schemes for smart grids are designed with the idea of security by agility. In particular, these schemes make the behavior unpredictable for the attacker by frequently randomizing various critical parameters in the smart grid system, whilst keeping it deterministic for the system. These techniques provide automatic analysis of security properties and synthesis of threat mitigation plans ensuring the security and resiliency of the system. This chapter summarizes the formal analytics presented in this book and presents an overview of the technical approach. Finally, it briefly discusses about the tools used for formal modeling. Formal AnalyticsThere are formal techniques and tools that can address the security requirements, identify potential threats, and offer remediation plans for smart grids, so that secure and reliable smart grids can be established. These techniques mostly focus on 2 Analytics for Smart Grid Security and Resiliency AMI, SCADA, and EMS, the most critical components of a smart grid ( Fig. 1.2). The formal analytics for smart grid security and resiliency falls can be described in the following three major categories: Security Analytics for AMI and SCADA A scalable and provable formal framework is presented that can verify the compliance of AMI configurations with NIST security guidelines [15], and generate remediation plans for potential security violations. This framework is implemented as a tool named SmartAnalyzer, which enables energy providers to proactively investigate AMI security configurations in order to identify and mitigate potential security threats and to guarantee AMI operational integrity and security requirements. The uniqueness of this framework lies in the formal modeling of novel security properties that are critical for the integrity and security of AMI. These security properties include different invariant and user-driven constraints, such as data overflow/overwrite protection, cyber bandwidth limitation, data integrity and confidentiality, assured report delivery, and data freshness. An identical formal model for the proactive security analysis of SCADA is also presented. This model ...