Towards anomaly detection in smart grids by combining Complex Events Processing and SNMP objects

06/28/2021
by   Massimiliano Leone Itria, et al.
0

This paper describes the architecture and the fundamental methodology of an anomaly detector, which by continuously monitoring Simple Network Management Protocol data and by processing it as complex-events, is able to timely recognize patterns of faults and relevant cyber-attacks. This solution has been applied in the context of smart grids, and in particular as part of a security and resilience component of the Information and Communication Technologies (ICT) Gateway, a middleware-based architecture that correlates and fuses measurement data from different sources (e.g., Inverters, Smart Meters) to provide control coordination and to enable grid observability applications. The detector has been evaluated through experiments, where we selected some representative anomalies that can occur on the ICT side of the energy distribution infrastructure: non-malicious faults (indicated by patterns in the system resources usage), as well as effects of typical cyber-attacks directed to the smart grid infrastructure. The results show that the detection is promisingly fast and efficient.

READ FULL TEXT
research
06/04/2023

Anomaly Detection Techniques in Smart Grid Systems: A Review

Smart grid data can be evaluated for anomaly detection in numerous field...
research
09/21/2022

Hybrid AI-based Anomaly Detection Model using Phasor Measurement Unit Data

Over the last few decades, extensive use of information and communicatio...
research
12/28/2022

Smart meter data processing: a showcase for simple and efficient textual processing

The increase in the production and collection of data from devices is an...
research
09/09/2022

On Specification-based Cyber-Attack Detection in Smart Grids

The transformation of power grids into intelligent cyber-physical system...
research
10/05/2021

An Approach of Replicating Multi-Staged Cyber-Attacks and Countermeasures in a Smart Grid Co-Simulation Environment

While the digitization of power distribution grids brings many benefits,...
research
09/27/2019

Modeling and Detection of Future Cyber-Enabled DSM Data Attacks using Supervised Learning

Demand-Side Management (DSM) is a vital tool that can be used to ensure ...
research
07/25/2014

Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification

Detecting faults in electrical power grids is of paramount importance, e...

Please sign up or login with your details

Forgot password? Click here to reset