A Distributed Cyber-Attack Detection Scheme With Application to DC Microgrids

Abstract

DC microgrids often present a hierarchical control architecture, requiring integration of communication layers. This leads to the possibility of malicious attackers disrupting the overall system. Motivated by this application, in this paper we present a distributed monitoring scheme to provide attackdetection capabilities for linear Large-Scale Systems. The proposed architecture relies on a Luenberger observer together with a bank of Unknown-Intput Observers (UIOs) at each subsystem, providing attack detection capabilities. We describe the architecture and analyze conditions under which attacks are guaranteed to be detected, and, conversely, when they are stealthy. Our analysis shows that some classes of attacks cannot be detected using either module independently; rather, by exploiting both modules simultaneously, we are able to improve the detection properties of the diagnostic tool as a whole. Theoretical results are backed up by simulations, where our method is applied to a realistic model of a low-voltage DC microgrid under attack.

Software-Defined Power Grids: A Survey on Opportunities and Taxonomy for Microgrids

“…Such information can be useful as researchers consider further integration of SDNenabled devices into the microgrid. Securing Communications stack 1) Network verification against security policies maintained by the controller global view [13] 2) Securing routing and transmission links via end-to-end encryption [2], [15] 3) Designing cyber-security protocols for integration in the communication stack [85] 4) Taking advantage of embedded security in wireless technologies [85] eg implementation of the secure by design concept [86] 5) Host authentication in data communications such as the implementation of a host-checker in the controller [87] Early attack detection 1) Advancement in pattern, anomaly and third party detection [15] 2) Anomaly detection based on machine learning approaches [88] 3) Distributed detection scheme using multiple state observers to minimize localized attacks (antistealth strategy) [89], [90] 4) Software-defined active synchronous detection (SDASD) [87] Early attack mitigation 1) Self-healing/ Self-recovery systems [4], [13], [91] 2) Increasing the signal to noise ratio to mitigate jamming [92] 3) Use of cryptographic signatures [93] 4) introduction of redundant communication link to be used during attacks [91] 5) introduction of ultra-fast network programmability [4] The DERs and associated loads in the microgrid can also be investigated for SDN control and support. Such support can enable close coupling between SDN controllers and the DERs/loads, ultimately increasing the management flexibility and efficiency.…”

Detection and Mitigation of False Data in Cooperative DC Microgrids With Unknown Constant Power Loads

“…Nonetheless, the design and implementation of the observer in each DGU requires the knowledge of the full DC microgrid, which complicates the incorporation of new DGUs in the system. A distributed estimation strategy was achieved by combining a bank of unknown input observers with a bank of linear Luenberger observers [19].…”

Distributed Event-Triggered Consensus-Based Control of DC Microgrids in Presence of DoS Cyber Attacks

“…DC microgrid systems rely on real-time operation and in presence of DoS cyber attacks may become unstable and damaged [41]. In [42], a distributed monitoring scheme for attack detection in large-scale linear systems applied to DC microgrids is presented. The recommended architecture utilizes a Luenberger observer as well as a bank of unknown-Input Observers at each subsystem to provide attack detection capabilities.…”