Cyber Security in Smart Grid: Challenges and Solutions

Rajendran, G.; Sathyabalu, Harsha Vardhan; Sachi, Meikandasivam; Devarajan, Vijayakumar

doi:10.1109/icpedc47771.2019.9036484

Cited by 14 publications

(12 citation statements)

References 13 publications

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“…Smart grid fraud has been a growing target for hackers. There are security and vulnerability concerns with the smart grid, according to this study (Rajendran et al, 2019;Fu, 2022). In the closing paragraphs, the attacks are addressed, and answers are offered.…”

Section: Related Workmentioning

confidence: 98%

Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models

Aziz¹,

Irshad

Haider

et al. 2022

Front. Energy Res.

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False data injection (FDI) attacks commonly target smart grids. Using the tools that are now available for detecting incorrect data, it is not possible to identify FDI attacks. One way that can be used to identify FDI attacks is machine learning. The purpose of this study is to analyse each of the six supervised learning (SVM-FS) hybrid techniques using the six different boosting and feature selection (FS) methodologies. A dataset from the smart grid is utilised in the process of determining the applicability of various technologies. Comparisons of detection strategies are made based on how accurately each one can identify different kinds of threats. The performance of classification algorithms that are used to detect FDI assaults is improved by the application of supervised learning and hybrid methods in a simulated exercise.

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Section: Related Workmentioning

confidence: 98%

Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models

Aziz¹,

Irshad

Haider

et al. 2022

Front. Energy Res.

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“…(3) Cyber-Physical Attack: IoT-based SG is the largest cyber-physical system, with physical components of Circuit Breakers (CB), transformers, and relays along with ICT components of sensors, and microcontrollers; it is more vulnerable to DoS attacks as compared to a traditional grid system, which is generally only physical and very difficult to reach. Any attack against the availability of service is called DoS [8]. These attacks directly impact the physical layer of the system, jamming the channel and causing immense loss.…”

Section: An Overview Of Smart Grid Security Challengesmentioning

confidence: 99%

Smart Grid Cyber Security Enhancement: Challenges and Solutions—A Review

2022

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The incorporation of communication technology with Smart Grid (SG) is proposed as an optimal solution to fulfill the requirements of the modern power system. A smart grid integrates multiple energy sources or microgrids and is supported by an extensive control and communication network using the Internet of Things (IoT) for a carbon-free, more reliable, and intelligent energy system. Along with many benefits, the system faces novel security challenges, data management, integration, and interoperability challenges. The advanced control and communication network in the smart grid is susceptible to cyber and cyber-physical threats. A lot of research has been done to improve the cyber security of the smart grid. This review aims to provide an overview of the types of cyber security threats present for smart grids with an insight into strategies to overcome the challenges. As the selection of techniques and technologies may vary according to the threats faced, therefore the adoption of researched methods is compared and discussed. As cyber-security is the greatest challenge in smart grid implementation, this review is beneficial during the planning and operation of smart grids for enhanced security.

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“…Although several techniques and frameworks have been proposed to tackle cyber attacks against power grids, it is worthy of note that there are some challenges that are drastically affecting their performance [1]. One major challenge is that of gaining access to relevant cyber attack data, availability of resources to quickly process the data and skills to do so.…”

Section: Problem Analysismentioning

confidence: 99%

“…The smart grid (SG) is a gigantic network spanning over a huge geographical area with heterogeneous communication network [1]. It has been undergoing rapid transformation in recent years due to the need to integrate renewable energy sources (distributed over a large geographical area) into the grid.…”

Section: Introductionmentioning

confidence: 99%

On Holistic Multi-Step Cyberattack Detection via a Graph-based Correlation Approach

Sen

Eze

Ulbig

et al. 2022

2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

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While digitization of distribution grids through information and communications technology brings numerous benefits, it also increases the grid's vulnerability to serious cyber attacks. Unlike conventional systems, attacks on many industrial control systems such as power grids often occur in multiple stages, with the attacker taking several steps at once to achieve its goal. Detection mechanisms with situational awareness are needed to detect orchestrated attack steps as part of a coherent attack campaign. To provide a foundation for detection and prevention of such attacks, this paper addresses the detection of multi-stage cyber attacks with the aid of a graph-based cyber intelligence database and alert correlation approach. Specifically, we propose an approach to detect multi-stage attacks by leveraging heterogeneous data to form a knowledge base and employ a model-based correlation approach on the generated alerts to identify multi-stage cyber attack sequences taking place in the network. We investigate the detection quality of the proposed approach by using a case study of a multi-stage cyber attack campaign in a future-orientated power grid pilot.

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Cyber Security in Smart Grid: Challenges and Solutions

Cited by 14 publications

References 13 publications

Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models

Protection of a smart grid with the detection of cyber- malware attacks using efficient and novel machine learning models

Smart Grid Cyber Security Enhancement: Challenges and Solutions—A Review

On Holistic Multi-Step Cyberattack Detection via a Graph-based Correlation Approach

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