Smart grid security: Attacks and defence techniques

Kim, Yoonjib; Hakak, Saqib; Ghorbani, Ali A.

doi:10.1049/stg2.12090

Cited by 29 publications

(9 citation statements)

References 72 publications

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“…As a result, cyber-security is considered a crucial component of SCADA [13,14], frequently used in power distribution networks to protect the security of regulated processes. The most critical element of the smart grid, the SCADA system, is responsible for securing communication protocols, asset management, physical infrastructures, and controlled operations [15,16]. These cannot be protected in the same way as modern IT systems.…”

Section: Introductionmentioning

confidence: 99%

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

Rabie

Balachandran²,

Shitharth

2022

Electronics

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Smart grids are complex cyber-physical systems that incorporate smart devices’ communication capabilities into the grid to enable remote management and the control of power systems. However, this integration reveals numerous SCADA system flaws, which could compromise security goals and pose severe cyber threats to the smart grid. In conventional works, various attack detection methodologies are developed to strengthen the security of smart grid SCADA systems. However, they have several issues with complexity, slow training speed, time consumption, and inaccurate prediction outcomes. The purpose of this work is to develop a novel security framework for protecting smart grid SCADA systems against harmful network vulnerabilities or intrusions. Therefore, the proposed work is motivated to develop an intelligent meta-heuristic-based Artificial Intelligence (AI) mechanism for securing IoT-SCADA systems. The proposed framework includes the stages of dataset normalization, Zaire Ebola Search Optimization (ZESO), and Deep Random Kernel Forest Classification (DRKFC). First, the original benchmarking datasets are normalized based on content characterization and category transformation during preprocessing. After that, the ZESO algorithm is deployed to select the most relevant features for increasing the training speed and accuracy of attack detection. Moreover, the DRKFC technique accurately categorizes the normal and attacking data flows based on the optimized feature set. During the evaluation, the performance of the proposed ZESO-DRKFC method is validated and compared in terms of accuracy, detection rate, f1-score, and false acceptance rate. According to the results, it is observed that the ZESO-DRKFC mechanism outperforms other techniques with high accuracy (99%) by precisely spotting intrusions in the smart grid systems.

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Section: Introductionmentioning

confidence: 99%

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

Rabie

Balachandran²,

Shitharth

2022

Electronics

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“…To underscore the significance of the presented covert channel in enhancing the security of the SG, we highlight the existing threats and attacks the smart grid is susceptible to. The extended research conducted in [32] provides a comprehensive taxonomical classification of attacks within the SG framework. It systematically delineates the various components, vulnerabilities, and corresponding countermeasures, revealing a total of 33 distinct vulnerabilities across SG components.…”

Section: Security Threatsmentioning

confidence: 99%

StegoBackoff: Creating a Covert Channel in Smart Grids Using the Backoff Procedure of IEEE 802.11 Networks

Teca,

Natkaniec

2024

Energies

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A smart grid constitutes an electrical infrastructure that integrates communication technologies to optimize electricity production, distribution, and consumption. Within the smart grid, IEEE 802.11 networks play a crucial role in facilitating communication between smart meters and data collectors, operating within a shared transmission medium. However, a notable challenge arises due to the lack of certainty regarding the genuine identity of data recipients. In response, we present a solution—a novel covert channel leveraging the IEEE 802.11 backoff procedure—to transmit data that requires special protection. Implemented using the ns-3 simulator, our covert channel achieved a throughput of 140,000 bps when single covert station realized transmission in the wireless channel, and 880 bps in a populated environment characterized by high traffic volumes. This performance metric shows that our mechanism is better than other covert channels, where the performance in saturated conditions usually does not exceed several hundred bps. This covert channel represents a new approach to fortifying data integrity and privacy within smart grid communication.

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“…Some of the standards for SG sensors are: Coordinated Universal Time Synchronization (UTC) and Exact Time. Fast data processing and intelligent algorithms (e.g., phase and frequency estimation, ROCOF from observed voltage, current, and time synchronization signals) [ 70 ]. Precision and sensitivity detect voltage, current, and phase angle [ 71 ].…”

Section: Preliminaries: Detailed Analysis Of the Literaturementioning

confidence: 99%

“…Coordinated Universal Time Synchronization (UTC) and Exact Time. Fast data processing and intelligent algorithms (e.g., phase and frequency estimation, ROCOF from observed voltage, current, and time synchronization signals) [ 70 ].…”

Section: Preliminaries: Detailed Analysis Of the Literaturementioning

confidence: 99%

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Binyamin

Slama

2022

Sensors

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Multi-Agent Systems (MAS) have been seen as an attractive area of research for civil engineering professionals to subdivide complex issues. Based on the assignment’s history, nearby agents, and objective, the agent intended to take the appropriate action to complete the task. MAS models complex systems, smart grids, and computer networks. MAS has problems with agent coordination, security, and work distribution despite its use. This paper reviews MAS definitions, attributes, applications, issues, and communications. For this reason, MASs have drawn interest from computer science and civil engineering experts to solve complex difficulties by subdividing them into smaller assignments. Agents have individual responsibilities. Each agent selects the best action based on its activity history, interactions with neighbors, and purpose. MAS uses the modeling of complex systems, smart grids, and computer networks. Despite their extensive use, MAS still confronts agent coordination, security, and work distribution challenges. This study examines MAS’s definitions, characteristics, applications, issues, communications, and evaluation, as well as the classification of MAS applications and difficulties, plus research references. This paper should be a helpful resource for MAS researchers and practitioners. MAS in controlling smart grids, including energy management, energy marketing, pricing, energy scheduling, reliability, network security, fault handling capability, agent-to-agent communication, SG-electrical cars, SG-building energy systems, and soft grids, have been examined. More than 100 MAS-based smart grid control publications have been reviewed, categorized, and compiled.

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Smart grid security: Attacks and defence techniques

Cited by 29 publications

References 72 publications

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

A Proficient ZESO-DRKFC Model for Smart Grid SCADA Security

StegoBackoff: Creating a Covert Channel in Smart Grids Using the Backoff Procedure of IEEE 802.11 Networks

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

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