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The IEC 61850 Sampled Measured Values Protocol: Analysis, Threat Identification, and Feasibility of Using NN Forecasters to Detect Spoofed Packets

Journal Article · · Energies
DOI:https://doi.org/10.3390/en12193731· OSTI ID:1801310
 [1];  [2];  [3];  [4];  [2];  [2]
  1. Florida International Univ., Miami, FL (United States). Dept. of Electrical and Computer Engineering; OSTI
  2. Florida International Univ., Miami, FL (United States). Dept. of Electrical and Computer Engineering
  3. Univ. of West Florida, Pensacola, FL (United States). Dept. of Electrical and Computer Engineering
  4. Florida Polytechnic Univ., Lakeland, FL (United States). Dept. of Electrical and Computer Engineering
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The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed.

Research Organization:
Univ. of Arkansas, Fayetteville, AR (United States)
Sponsoring Organization:
USDOE Office of Electricity Delivery and Energy Reliability (OE)
Grant/Contract Number:
OE0000779
OSTI ID:
1801310
Journal Information:
Energies, Journal Name: Energies Journal Issue: 19 Vol. 12; ISSN 1996-1073
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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Real-Time Performance and Security of IEC 61850 Process Bus Communications journal April 2021

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Related Subjects

97 MATHEMATICS AND COMPUTING
IEC 61850
artificial intelligence
attack detection
cyber security
forecasting
message spoofing
microgrid
neural networks
process bus
sampled measured values