Data-driven power system security assessment using high content database during the COVID-19 pandemic

Mollaiee, Ali; Ameli, Mohammad Taghi; Azad, Sasan; Nazari-Heris, Morteza; Asadi, Somayeh

doi:10.1016/j.ijepes.2023.109077

Cited by 9 publications

(3 citation statements)

References 30 publications

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“…A CSRAM also addressed the establishment of the information security policy development team, determining the security needs of the organization, compiling the security policy document, and the implementation and maintenance phases in [18]. Based on the same scenarios conducted for [4] [16] [19]- [25] [65] [70], the developed CSRAM covered all processes for these models from start to finish. Table 3 compares the CSRAM with the existing studies.…”

Section: Resultsmentioning

confidence: 99%

“…Information security risk assessment, implementation of security controls, monitoring, and review 12 2023 [70] This research emphasizes the broadening attack surface for threat actors due to IoT firmware security risks. Denial-of-service and brute-force attacks, which are common in diverse smart home environments, can no longer be countered by firewall rules that prevent denial-of-service attacks or brute force attacks.…”

Section: Development Process Of the Csrammentioning

confidence: 99%

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Towards Development of a Security Risk Assessment Model for Saudi Arabian Business Environment Based on the ISO/IEC 27005 ISRM Standard

Alheadary¹

2023

JIS

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Security risk assessment refers to the process of identifying, analyzing, and evaluating potential security risks for an organization. An organization's assets, personnel, and operations are protected through it as part of a comprehensive security program. Various security assessments models have been published in the literature to protect the Saudi organization's assets, personnel, and operations. However, these models are redundant and were developed for specific purposes. Hence, the comprehensive security risk assessment model used to safeguard Saudi organizations' assets, personnel, and operations is still omitted. Using a design science methodology, the objective of this study is to develop a comprehensive security risk assessment model called CSRAM to assess security risks in Saudi Arabian organizations based on the International Organization for Standardization and the International Electrotechnical Commission/Information security risk management (ISO/IEC 27005 ISRM) standard. CSRAM is made up of six stages: threat identification, vulnerability assessment, risk analysis, risk evaluation, risk treatment, and monitoring and review of the risk. The stages have many activities and tasks that need to be accomplished at each stage. Based on the results of the validation of the completeness of the CSRAM, we can say that the CSRAM covers the whole ISO/IEC 27005 ISRM standard, and it is complete.

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Section: Resultsmentioning

confidence: 99%

Section: Development Process Of the Csrammentioning

confidence: 99%

Towards Development of a Security Risk Assessment Model for Saudi Arabian Business Environment Based on the ISO/IEC 27005 ISRM Standard

Alheadary¹

2023

JIS

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“…In such conditions, an under-stressed system can lose its dynamic security when faced with a severe contingency. As a result, cascading outages and widespread blackouts may occur [1,2]. Therefore, DSA is necessary for a stable and continuous power supply in the power systems [3,4].…”

Section: Introductionmentioning

confidence: 99%

A domain adaptation‐based convolutional neural network incorporating data augmentation for power system dynamic security assessment

Azad,

Ameli

2024

The Journal of Engineering

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Recently, deep learning (DL) based dynamic security assessment (DSA) methods have been very successful. However, although a DSA model can be trained well for a specific topology, it often does not perform well for other topologies. Since the topology in real‐world power systems is frequently changing, the performance reduction of DL‐based DSA methods is very serious, which is a challenging and urgent problem. This paper proposes a novel DSA method based on a convolutional neural network (CNN) to solve this problem. In the proposed method, a strong yet simple domain adaptation approach named adaptive batch normalization (AdaBN) is used, which significantly enhances the extensibility and generalizability of the DSA model when the topology changes and eliminates the need to train a large number of models. This approach achieves a deep adaptation effect by modulating the statistics from the source domain to the target domain in all batch normalization layers across the model. Unlike other domain adaptation methods, this method is parameter‐free, requires no additional components, and has advanced performance despite its simplicity. In addition, this paper introduces TGAN‐based data augmentation to deal with the difficulty of costly data collection and labelling. This data augmentation makes the proposed model applicable to small databases. The test results of the proposed method on IEEE 39‐bus and IEEE 118‐bus systems show that this method can evaluate system dynamic security during topology changes and in the face of data noise with high accuracy.

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Digital Twin-Integrated Data-Driven Approach for Security Assessment in Modern Power Systems

Rahmani-Sane,

Azad,

Mosallanejad

et al. 2024

Power Systems

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Data-driven power system security assessment using high content database during the COVID-19 pandemic

Cited by 9 publications

References 30 publications

Towards Development of a Security Risk Assessment Model for Saudi Arabian Business Environment Based on the ISO/IEC 27005 ISRM Standard

Towards Development of a Security Risk Assessment Model for Saudi Arabian Business Environment Based on the ISO/IEC 27005 ISRM Standard

A domain adaptation‐based convolutional neural network incorporating data augmentation for power system dynamic security assessment

Digital Twin-Integrated Data-Driven Approach for Security Assessment in Modern Power Systems

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