A lightweight approach towards mutual authentication in a smart grid environment

Smart grids allow automated meter readings and facilitate two-way communications between the smart meters and utility control centers. As the smart grid becomes more intelligent, it becomes increasingly vulnerable to cyber-attacks. Smart grid security mainly focuses on mutual authentication and key management techniques. An impeding factor in grid security is the memory and processing constraints of the smart meters. The aim of this thesis is to propose a lightweight mutual authentication protocol with an effective key renewal mechanism between a residential smart meter and a gateway. The authentication protocol proposed in the thesis, guarantees source authentication, data integrity, message confidentiality, as well as non-repudiation. The security analysis renders this protocol robust against several attacks. Furthermore, its performance analysis provides meticulous results as to how the proposed protocol is efficient in terms of computation overhead, average delay and buffer occupancy at the gateway.

A lightweight approach towards mutual authentication in a smart grid environment

Smart grids allow automated meter readings and facilitate two-way communications between the smart meters and utility control centers. As the smart grid becomes more intelligent, it becomes increasingly vulnerable to cyber-attacks. Smart grid security mainly focuses on mutual authentication and key management techniques. An impeding factor in grid security is the memory and processing constraints of the smart meters. The aim of this thesis is to propose a lightweight mutual authentication protocol with an effective key renewal mechanism between a residential smart meter and a gateway. The authentication protocol proposed in the thesis, guarantees source authentication, data integrity, message confidentiality, as well as non-repudiation. The security analysis renders this protocol robust against several attacks. Furthermore, its performance analysis provides meticulous results as to how the proposed protocol is efficient in terms of computation overhead, average delay and buffer occupancy at the gateway.

Reliability of Smart Grid Including Cyber Impact

Smart grid has changed power systems and their reliability concerns. Along with that, cyber security issues are also introduced due to the use of intelligent electronic devices (IEDs), wireless sensory network (WSN), and internet of things (IoT) for two-way communication. This chapter presents a review of different methods used from 2010 to 2020 focusing on citation as the main criteria for reliability assessment of smart grids and proposals to improve reliability when it comes to assessing a practical transmission system. It shows that evolutionary techniques are the latest trend for smart grid security.

GridAttackSim: A Cyber Attack Simulation Framework for Smart Grids

The smart grid system is one of the key infrastructures required to sustain our future society. It is a complex system that comprises two independent parts: power grids and communication networks. There have been several cyber attacks on smart grid systems in recent years that have caused significant consequences. Therefore, cybersecurity training specific to the smart grid system is essential in order to handle these security issues adequately. Unfortunately, concepts related to automation, ICT, smart grids, and other physical sectors are typically not covered by conventional training and education methods. These cybersecurity experiences can be achieved by conducting training using a smart grid co-simulation, which is the integration of at least two simulation models. However, there has been little effort to research attack simulation tools for smart grids. In this research, we first review the existing research in the field, and then propose a smart grid attack co-simulation framework called GridAttackSim based on the combination of GridLAB-D, ns-3, and FNCS. The proposed architecture allows us to simulate smart grid infrastructure features with various cybersecurity attacks and then visualize their consequences automatically. Furthermore, the simulator not only features a set of built-in attack profiles but also enables scientists and electric utilities interested in improving smart grid security to design new ones. Case studies were conducted to validate the key functionalities of the proposed framework. The simulation results are supported by relevant works in the field, and the system can potentially be deployed for cybersecurity training and research.