Self-Healing Secure Blockchain Framework in Microgrids

TL;DR

This paper introduces a self-healing, secure blockchain framework for microgrids that detects and recovers from stealth attacks, malware, and communication delays using physics-informed methods and predictive control.

Contribution

It presents a novel integrated approach combining blockchain security, physics-informed malware detection, and self-healing recovery for microgrid cyber-physical systems.

Findings

Enhanced detection of stealth consensus attacks

Effective recovery of compromised nodes

Robustness against communication delays and DoS attacks

Abstract

Blockchain has recently been depicted as a secure protocol for information exchange in cyber-physical microgrids. However, it is still found vulnerable to consensus manipulation attacks. These stealth attacks are often difficult to detect as they use kernel-level access to mask their actions. In this paper, we firstly build a trusted and secured peer-to-peer network mechanism for physical DC microgrids' validation of transactions over Distributed Ledger. Secondly, we leverage from a physics-informed approach for detecting malware-infected nodes and then recovering from stealth attacks using a self-healing recovery scheme augmented into the microgrid Blockchain network. This scheme allows compromised nodes to adapt to a reconstructed trustworthy signal in a multi-hop manner using corresponding measurements from the reliable nodes in the network. Additionally, recognizing the possible threat of denial-of-service attacks and random time delays (where information sharing via communication channels is blocked), we also integrate a model-free predictive controller with the proposed system that can locally reconstruct an expected version of the attacked/delayed signals. This supplements the capabilities of Blockchain, enabling it to detect and mitigate consensus manipulation attempts, and network latencies.