Ontology-based approach for malicious behaviour detection in synchrophasor networks

Albalushi, Abdullah; Khan, Rafiullah; McLaughlin, Kieran; Sezer, Sakir

doi:10.1109/pesgm.2017.8274684

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…An ontology-based detection of cyberattacks in SCADA systems is presented in [85]. The authors in [86] proposed an ontology-based scheme on synchrophasor communication to detect malicious command injection in the smart grid.…”

Section: B Model-based Detectionmentioning

confidence: 99%

Command Injection Attacks in Smart Grids: A Survey

Usama,

Aman

2024

IEEE Open J. Ind. Applicat.

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Cybersecurity is important in the realization of various smart grid technologies. Several studies have been conducted to discuss different types of cyberattacks and provide their countermeasures. The False Command Injection Attack (FCIA) is considered one of the most critical attacks that have been studied. Various techniques have been proposed in the literature to detect FCIAs on different components of smart grids. The predominant focus of current surveys lies on FCIAs and detection techniques for such attacks. This paper presents a survey of existing works on FCIAs and classifies FCIAs in smart grids according to the targeted component. The impacts of FCIAs on smart grids are also discussed. Subsequently, this paper provides an extensive review of detection studies, categorizing them based on the type of detection technique employed.

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Section: B Model-based Detectionmentioning

confidence: 99%

Command Injection Attacks in Smart Grids: A Survey

Usama,

Aman

2024

IEEE Open J. Ind. Applicat.

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“…To a lesser extent, the use of languages such as SPARQL, SWRL, XML and OWL 2 is observed (Baesso Moreira et al, 2019;Onwubiko et al, 2018;Albalushi et al, 2018;Tseng et al, 2017;Bergner and Lechner, 2017;Fontenele and Sun, 2016;Maines et al, 2015;Geller et al, 2014).…”

Section: Table 5 Ontology Classification By Used Toolsmentioning

confidence: 99%

Cybersecurity Ontologies: A Systematic LiteratureReview

Rivadeneira¹,

Gómez

de³

2021

recibe

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Cybersecurity is a young discipline that has gained relevance in our modern society.Thisresearchreportsthefindingsofasystematicreviewoftheliteratureonontologiesinthefieldofcybersecurity. From an initial set of 214 papers on the subject, 50 relevant papers were selected forthis SLR. With these documents we answered research questions related to the domains in whichontologies are reported, the methodologies, tools and languages used, and the verification andvalidation mechanisms reported. As results, we observed that the largest number of ontologies areclassified in the domains of infrastructure and networking, software and human factor. Regardingthe papers that report the use of a methodology for developing the ontologies (12%), Methontologyis the commonly used one. Protégé, in conjunction with the OWL language, are the preferred toolsfor ontology development. Regarding verification and validation (V&V) mechanisms, we observethat morethanhalf(62%) reporttheapplicationofV&Vmechanisms totheir ontologies.

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Security Risk Modeling in Smart Grid Critical Infrastructures in the Era of Big Data and Artificial Intelligence

2021

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Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The current security tools are almost perfect when it comes to identifying and preventing known attacks in the smart grid. Still, unfortunately, they do not quite meet the requirements of advanced cybersecurity. Adequate protection against cyber threats requires a whole set of processes and tools. Therefore, a more flexible mechanism is needed to examine data sets holistically and detect otherwise unknown threats. This is possible with big modern data analyses based on deep learning, machine learning, and artificial intelligence. Machine learning, which can rely on adaptive baseline behavior models, effectively detects new, unknown attacks. Combined known and unknown data sets based on predictive analytics and machine intelligence will decisively change the security landscape. This paper identifies the trends, problems, and challenges of cybersecurity in smart grid critical infrastructures in big data and artificial intelligence. We present an overview of the SG with its architectures and functionalities and confirm how technology has configured the modern electricity grid. A qualitative risk assessment method is presented. The most significant contributions to the reliability, safety, and efficiency of the electrical network are described. We expose levels while proposing suitable security countermeasures. Finally, the smart grid’s cybersecurity risk assessment methods for supervisory control and data acquisition are presented.

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Ontology-based approach for malicious behaviour detection in synchrophasor networks

Cited by 3 publications

References 14 publications

Command Injection Attacks in Smart Grids: A Survey

Command Injection Attacks in Smart Grids: A Survey

Cybersecurity Ontologies: A Systematic LiteratureReview

Security Risk Modeling in Smart Grid Critical Infrastructures in the Era of Big Data and Artificial Intelligence

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