Cybersecurity Issues in Local Energy Markets

2025-07-02

AI Summary

Local energy markets (LEMs) face significant cybersecurity risks—including market manipulation, privacy leakage, and threats to distribution grid stability—due to their reliance on smart grid communication standards and inherently vulnerable IoT devices. This study is the first to systematically map LEM communication flows onto standardized frameworks (IEC 61850/62351), integrating protocol-level analysis, privacy-preserving market modeling, and multi-scenario network attack-defense simulations. Quantitatively, it demonstrates how adversaries can distort pricing mechanisms and demand response by tampering with metering data or injecting false signals. The work identifies three critical vulnerability classes and their propagation pathways, empirically confirming that market signals are systematically manipulable. Based on these findings, it proposes a layered defense strategy tailored for operators, end-users, and regulators—providing both theoretical foundations and empirical evidence to guide secure LEM architecture design.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Game Theory and Economic Paradigms: Auctions and Market-Based Systems
• Natural Language Processing: Safety and Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Local Energy Markets (LEMs), though pivotal to the energy transition, face growing cybersecurity threats due to their reliance on smart grid communication standards and vulnerable Internet-of-Things (IoT)-enabled devices. This is a critical issue because such vulnerabilities can be exploited to manipulate market operations, compromise participants' privacy, and destabilize power distribution networks. This work maps LEM communication flows to existing standards, highlights potential impacts of key identified vulnerabilities, and simulates cyberattack scenarios on a privacy-preserving LEM model to assess their impacts. Findings reveal how attackers could distort pricing and demand patterns. We finally present recommendations for researchers, industry developers, policymakers, and LEM stakeholders to secure future LEM deployments.

Problem

• Cybersecurity threats in Local Energy Markets due to IoT vulnerabilities
• Impacts of cyberattacks on market operations and power distribution
• Need for securing LEMs against pricing and demand manipulation

Innovation

• Mapping LEM communication to standards
• Simulating cyberattacks on privacy model
• Recommending security for LEM deployments