Pub Date : 2021-02-11DOI: 10.1109/SmartGridComm51999.2021.9632338
J. Janak, D. Chee, Hema Retty, A. Baloian, H. Schulzrinne
When the electrical grid in a region suffers a major outage, e.g., after a catastrophic cyber attack, a “black start” may be required, where the grid is slowly restarted, carefully and incrementally adding generating capacity and demand. To ensure safe and effective black start, the grid control center has to be able to communicate with field personnel and with supervisory control and data acquisition (SCADA) systems. Voice and text communication are particularly critical. As part of the Defense Advanced Research Projects Agency (DARPA) Rapid Attack Detection, Isolation, and Characterization Systems (RADICS) program, we designed, tested and evaluated a self-configuring mesh network prototype called the Phoenix Secure Emergency Network (PhoenixSEN). PhoenixSEN provides a secure drop-in replacement for grid's primary communication networks during black start recovery. The network combines existing and new technologies, can work with a variety of link-layer protocols, emphasizes manageability and auto-configuration, and provides services and applications for coordination of people and devices including voice, text, and SCADA communication. We discuss the architecture of PhoenixSEN and evaluate a prototype on realistic grid infrastructure through a series of DARPA-led exercises.
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Pub Date : 2019-06-11DOI: 10.1109/SmartGridComm51999.2021.9631987
Yize Chen, Yushi Tan, Ling Zhang, Baosen Zhang
We study the security threats of power system operations from a class of data injection attacks on load forecasting algorithms. In particular, we design an attack strategy on input features for load forecasting algorithms which can be implemented by an attacker with minimal system knowledge. System operators can be oblivious of such wrong load forecasts, which lead to uneconomical or even insecure decisions in commitment and dispatch. This paper brings up the security issues of load forecasting algorithms and shows that accurate load forecasting algorithm is not necessarily robust to malicious attacks. If power grid topology information is exploited, more severe attacks can be designed. We demonstrate the impact of load forecasting attacks on two IEEE test cases. We show our attack strategy is able to cause load shedding with high probability under various settings in the 14-bus test case, and also demonstrate system-wide threats in the 118-bus test case with limited local attacks.
{"title":"Vulnerabilities of Power System Operations to Load Forecasting Data Injection Attacks","authors":"Yize Chen, Yushi Tan, Ling Zhang, Baosen Zhang","doi":"10.1109/SmartGridComm51999.2021.9631987","DOIUrl":"https://doi.org/10.1109/SmartGridComm51999.2021.9631987","url":null,"abstract":"We study the security threats of power system operations from a class of data injection attacks on load forecasting algorithms. In particular, we design an attack strategy on input features for load forecasting algorithms which can be implemented by an attacker with minimal system knowledge. System operators can be oblivious of such wrong load forecasts, which lead to uneconomical or even insecure decisions in commitment and dispatch. This paper brings up the security issues of load forecasting algorithms and shows that accurate load forecasting algorithm is not necessarily robust to malicious attacks. If power grid topology information is exploited, more severe attacks can be designed. We demonstrate the impact of load forecasting attacks on two IEEE test cases. We show our attack strategy is able to cause load shedding with high probability under various settings in the 14-bus test case, and also demonstrate system-wide threats in the 118-bus test case with limited local attacks.","PeriodicalId":378884,"journal":{"name":"2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130058951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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