Abstract
Modern power systems require increased connectivity to implement novel coordination and control schemes. Wide-spread use of information technology in smartgrid domain is an outcome of this need. IEC 61850-based communication solutions have become popular due to a myriad of reasons. Object-oriented modeling capability, interoperable connectivity and strong communication protocols are to name a few. However, power system communication infrastructure is not well-equipped with cybersecurity mechanisms for safe operation. Unlike online banking systems that have been running such security systems for decades, smartgrid cybersecurity is an emerging field. A recent publication aimed at equipping IEC 61850-based communication with cybersecurity features, i.e. IEC 62351, only focuses on communication layer security. To achieve security at all levels, operational technology-based security is also needed. To address this need, this paper develops an intrusion detection system for smartgrids utilizing IEC 61850‘s Sampled Value (SV) messages. The system is developed with machine learning and is able to monitor communication traffic of a given power system and distinguish normal data measurements from falsely injected data, i.e. attacks. The designed system is implemented and tested with realistic IEC 61850 SV message dataset. Tests are performed on a Modified IEEE 14-bus system with renewable energy-based generators where different fault are applied. The results show that the proposed system can successfully distinguish normal power system events from cyberattacks with high accuracy. This ensures that smartgrids have intrusion detection in addition to cybersecurity features attached to exchanged messages.
Highlights
Integration of Information Technology (IT) with power systems gave birth to smartgrids [1]
This paper develops a machine learning-based intrusion detection system for Sampled Value (SV) messages
Based on the nature of SV messages, the system is able to differentiate between usual operation from attacks
Summary
Integration of Information Technology (IT) with power systems gave birth to smartgrids [1]. Results are reported to discuss which one of these algorithms is more suitable for intrusion detection in power system communication based on IEC 61850 SV messages. IEC 62351 cybersecurity standard only recommends use of communication layer security mechanisms, such as implementing hash algorithms to check message integrity or using digital signatures to authenticate senders. MACHINE-LEARNING BASED INTRUSION DETECTION ALGORITHM SV messages are giving a snapshot of the entire power system by continuously sampling system parameters and sending them to control centers. These system parameters change with respect to events taking place in network such as load increase, generation loss or faults. Section presents the training data, test data and the test results for all the algorithms discussed above
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
