Vulnerability and Impact Analysis of the IEC 61850 GOOSE Protocol in the Smart Grid

Abstract

IEC 61850 is one of the most prominent communication standards adopted by the smart grid community due to its high scalability, multi-vendor interoperability, and support for several input/output devices. Generic Object-Oriented Substation Events (GOOSE), which is a widely used communication protocol defined in IEC 61850, provides reliable and fast transmission of events for the electrical substation system. This paper investigates the security vulnerabilities of this protocol and analyzes the potential impact on the smart grid by rigorously analyzing the security of the GOOSE protocol using an automated process and identifying vulnerabilities in the context of smart grid communication. The vulnerabilities are tested using a real-time simulation and industry standard hardware-in-the-loop emulation. An in-depth experimental analysis is performed to demonstrate and verify the security weakness of the GOOSE publish-subscribe protocol towards the substation protection within the smart grid setup. It is observed that an adversary who might have familiarity with the substation network architecture can create falsified attack scenarios that can affect the physical operation of the power system. Extensive experiments using the real-time testbed validate the theoretical analysis, and the obtained experimental results prove that the GOOSE-based IEC 61850 compliant substation system is vulnerable to attacks from malicious intruders.

Cyber-Physical Vulnerability Assessment in Smart Grids Based on Multilayer Complex Networks

“…where ⊕ α A [α] is the intra-layer adjacency matrix and ⊕ α,β A [α,β] is the inter-layer adjacency matrix corresponding to the connectivity matrix C. Figure 1 presents an example of a system with two layers; the physical layer contains two OT nodes (1,2) and the cyber layer comprises three IT nodes (3, 4, and 5). The intralayer adjacency matrices, corresponding to each layer as well as the intra-layer matrix, are defined by the matrices A [1] (4), A [2] (5), and ⊕ α A [α] (6). Similarly, the connectivity matrix between the layers is expressed by C (7), and it is obtained from the inter-layer adjacency matrices A [1,2] (8), where A [2,1] = A [1,2]T .…”

“…The intralayer adjacency matrices, corresponding to each layer as well as the intra-layer matrix, are defined by the matrices A [1] (4), A [2] (5), and ⊕ α A [α] (6). Similarly, the connectivity matrix between the layers is expressed by C (7), and it is obtained from the inter-layer adjacency matrices A [1,2] (8), where A [2,1] = A [1,2]T . Finally, the supra-adjacency matrix corresponding to the multilayer system in Figure 1 is represented by A M (9).…”

“…where ⨁ is the intra-layer adjacency matrix and ⨁ , , is the inter-layer adjacency matrix corresponding to the connectivity matrix . Figure 1 presents an example of a system with two layers; the physical layer contains two OT nodes (1,2) and the cyber layer comprises three IT nodes (3, 4, and 5). The intralayer adjacency matrices, corresponding to each layer as well as the intra-layer matrix, are defined by the matrices (4), (5), and ⨁ (6).…”

“…Smart grids are characterized by high digitisation that facilitates modernisation in electrical network infrastructure, active grid management, control and real-time communication with consumers, prosumers, and DSOs [ 1 ]. Smart grid digitisation has created new areas of work, in which the electrical and communications infrastructures are neither independent nor operate in isolation [ 2 , 3 ].…”

“…Vulnerability analysis allows power network operators to improve the robustness of critical elements in the network and develop countermeasures against untimely failures [ 6 ]. Therefore, recognising the most vulnerable elements in a power grid will result in better operation [ 1 , 7 ] and provide an indispensable tool for DSO decision-makers [ 8 ].…”