Securing the Smart Grid: A Comprehensive Compilation of Intrusion Detection and Prevention Systems

Radoglou-Grammatikis, Panagiotis; Sarigiannidis, Panagiotis

doi:10.1109/access.2019.2909807

Cited by 184 publications

(120 citation statements)

References 129 publications

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“…Delay-sensitive and time-critical operation requirement is another reason to consider employing an IDS/IPS specifically designed for the SG. In [136] authors gave brief overview on IDS/IPS systems that aim to secure AMI, SCADA, substations and synchrophasors.…”

Section: Intrusion Detection/preventionmentioning

confidence: 99%

A Survey of Denial-of-Service Attacks and Solutions in the Smart Grid

et al. 2020

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The scope, scale, and intensity of real, as well as potential attacks, on the Smart Grid have been increasing and thus gaining more attention. An important component of Smart Grid cybersecurity efforts addresses the availability and access to the power and related information and communications infrastructures. We overload the term, Denial-of-Service (DoS), to refer to these attacks in the Smart Grid. In this paper, we provide a holistic and methodical presentation of the DoS attack taxonomies as well as a survey of potential solution techniques to help draw a more concerted and coordinated research into this area, lack of which may have profound consequences. To the best of our knowledge, the literature does not have such a comprehensive survey study of the DoS attacks and solutions for the Smart Grid. INDEX TERMS Denial-of-Service attacks, Smart grid security, Cybersecurity I. ACRONYMS In order to make the paper more clear and easier to read, we provide a table of acronyms in Table 1

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Section: Intrusion Detection/preventionmentioning

confidence: 99%

A Survey of Denial-of-Service Attacks and Solutions in the Smart Grid

et al. 2020

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“…IDS can be applicable in many different application areas. In one of the current researches [5] authors focused on the security operations of smart grids. In this manner they mainly analyzed the 37 different cases in the intrusion detection and prevention systems concepts in smart grid environments One of the recent works is presented by Farahnakian and Heikkonen in 2018, and they prefer the used of deep learning approach for IDSs with the use of Deep Auto-Encoder model.…”

Section: Related Workmentioning

confidence: 99%

A Clustering Approach for Intrusion Detection with Big Data Processing on Parallel Computing Platform

Şahingöz

2019

Balkan Journal of Electrical and Computer Engineering

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In recent years there is a growing number of attacks in the computer networks. Therefore, the use of a prevention mechanism is an inevitable need for security admins. Although firewalls are preferred as the first layer of protection, it is not sufficient for preventing lots of the attacks, especially from the insider attacks. Intrusion Detection Systems (IDSs) have emerged as an effective solution to these types of attacks. For increasing the efficiency of the IDS system, a dynamic solution, which can adapt itself and can detect new types of intrusions with a dynamic structure by the use of learning algorithms is mostly preferred. In previous years, some machine learning approaches are implemented in lots of IDSs. In the current position of artificial intelligence, most of the learning systems are transferred with the use of Deep Learning approaches due to its flexibility and the use of Big Data with high accuracy. In this paper, we propose a clustered approach to detect the intrusions in a network. Firstly, the system is trained with Deep Neural Network on a Big Data set by accelerating its performance with the use of CUDA architecture. Experimental results show that the proposed system has a very good accuracy rate and low runtime duration with the use of this parallel computation architecture. Additionally, the proposed system needs a relatively small duration for training the system

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“…With the informationization upgrade of power companies and the promotion of the construction of energy Internet, power generation enterprises are accelerating the integration of the Internet [1]. The increase in production efficiency has also caused new security issues: the internal network of the smart grid is increasingly connected to the Internet, and the threats and attacks on the smart grid are becoming increasingly serious [2,3]. In order to ensure the security of the smart grid, the SGMS devices will record abnormal data (such as abnormal access data, a large number of DHCP service access), abnormal behavior (such as port scan, illegal access) and abnormal state (such as CPU, memory usage exceeds threshold) as a security event in the form of an alert log.…”

Section: Introductionmentioning

confidence: 99%

Critical Events Detection Based on Alert Logs in Smart Grid

Li¹,

Zhao²,

Jiao³

et al. 2019

Proceedings of the 2019 International Conference on Big Data, Electronics and Communication Engineering (BDECE 2019)

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Alert logs in the smart grid come from a variety of security devices and hosts. There are a large number of false alerts and low-threat alerts in the massive logs, which not only make the real threat difficult to be discovered, but also increase the difficulty of analysis. Therefore, based on the fact that there are anomalies in the process of the outbreak of security events, the concept of critical events and the critical event detection model in smart grid based on statistical analysis are proposed. The statistical analysis method is combined with the security event logs and the critical events detection algorithm is designed. The result from real data in the smart grid shows that the model can effectively detect critical events with an accuracy rate of 98%.

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Securing the Smart Grid: A Comprehensive Compilation of Intrusion Detection and Prevention Systems

Cited by 184 publications

References 129 publications

A Survey of Denial-of-Service Attacks and Solutions in the Smart Grid

A Survey of Denial-of-Service Attacks and Solutions in the Smart Grid

A Clustering Approach for Intrusion Detection with Big Data Processing on Parallel Computing Platform

Critical Events Detection Based on Alert Logs in Smart Grid

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