Real time security assessment of the power system using a hybrid support vector machine and multilayer perceptron neural network algorithms
- Alimi, Oyeniyi Akeem, Ouahada, Khmaies, Abu-Mahfouz, Adnan M.
- Authors: Alimi, Oyeniyi Akeem , Ouahada, Khmaies , Abu-Mahfouz, Adnan M.
- Date: 2019
- Subjects: Multilayer perceptron neural network , Support vector machine , Cyberattacks
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/404703 , uj:33952 , Citation : Alimi, O.A., Abu-Mahfouz, A.M., Ouahada, K. : 2019. Real time security assessment of the power system using a hybrid support vector machine and multilayer perceptron neural network algorithms.
- Description: Abstract : In today’s grid, the technological based cyber-physical systems have continued to be plagued with cyberattacks and intrusions. Any intrusive action on the power system’s Optimal Power Flow (OPF) modules can cause a series of operational instabilities, failures, and financial losses. Real time intrusion detection has become a major challenge for the power community and energy stakeholders. Current conventional methods have continued to exhibit shortfalls in tackling these security issues. In order to address this security issue, this paper proposes a hybrid Support Vector Machine and Multilayer Perceptron Neural Network (SVMNN) algorithm that involves the combination of Support Vector Machine (SVM) and multilayer perceptron neural network (MPLNN) algorithms for predicting and detecting cyber intrusion attacks into power system networks. In this paper, a modified version of the IEEE Garver 6-bus test system and a 24-bus system were used as case studies. The IEEE Garver 6-bus test system was used to describe the attack scenarios, whereas load flow analysis was conducted on real time data of a modified Nigerian 24-bus system to generate the bus voltage dataset that considered several cyberattack events for the hybrid algorithm. Sising various performance metricion and load/generator injections, en included in the manuscriptmulation results showed the relevant influences of cyberattacks on power systems in terms of voltage, power, and current flows. To demonstrate the performance of the proposed hybrid SVMNN algorithm, the results are compared with other models in related studies. The results demonstrated that the hybrid algorithm achieved a detection accuracy of 99.6%, which is better than recently proposed schemes.
- Full Text:
- Authors: Alimi, Oyeniyi Akeem , Ouahada, Khmaies , Abu-Mahfouz, Adnan M.
- Date: 2019
- Subjects: Multilayer perceptron neural network , Support vector machine , Cyberattacks
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/404703 , uj:33952 , Citation : Alimi, O.A., Abu-Mahfouz, A.M., Ouahada, K. : 2019. Real time security assessment of the power system using a hybrid support vector machine and multilayer perceptron neural network algorithms.
- Description: Abstract : In today’s grid, the technological based cyber-physical systems have continued to be plagued with cyberattacks and intrusions. Any intrusive action on the power system’s Optimal Power Flow (OPF) modules can cause a series of operational instabilities, failures, and financial losses. Real time intrusion detection has become a major challenge for the power community and energy stakeholders. Current conventional methods have continued to exhibit shortfalls in tackling these security issues. In order to address this security issue, this paper proposes a hybrid Support Vector Machine and Multilayer Perceptron Neural Network (SVMNN) algorithm that involves the combination of Support Vector Machine (SVM) and multilayer perceptron neural network (MPLNN) algorithms for predicting and detecting cyber intrusion attacks into power system networks. In this paper, a modified version of the IEEE Garver 6-bus test system and a 24-bus system were used as case studies. The IEEE Garver 6-bus test system was used to describe the attack scenarios, whereas load flow analysis was conducted on real time data of a modified Nigerian 24-bus system to generate the bus voltage dataset that considered several cyberattack events for the hybrid algorithm. Sising various performance metricion and load/generator injections, en included in the manuscriptmulation results showed the relevant influences of cyberattacks on power systems in terms of voltage, power, and current flows. To demonstrate the performance of the proposed hybrid SVMNN algorithm, the results are compared with other models in related studies. The results demonstrated that the hybrid algorithm achieved a detection accuracy of 99.6%, which is better than recently proposed schemes.
- Full Text:
Overlay virtualized wireless sensor networks for application in industrial internet of things : a review
- Nkomo, Malvin, Hancke, Gerhard P., Abu-Mahfouz, Adnan M., Sinha, Saurabh, Onumanyi, Adeiza. J.
- Authors: Nkomo, Malvin , Hancke, Gerhard P. , Abu-Mahfouz, Adnan M. , Sinha, Saurabh , Onumanyi, Adeiza. J.
- Date: 2018
- Subjects: Internet of Things , WSN virtualization , Overlay WSN
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278612 , uj:29901 , Citation: Nkomo, M. et al. 2018. Overlay virtualized wireless sensor networks for application in industrial internet of things : a review.
- Description: Abstract: In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field.
- Full Text:
- Authors: Nkomo, Malvin , Hancke, Gerhard P. , Abu-Mahfouz, Adnan M. , Sinha, Saurabh , Onumanyi, Adeiza. J.
- Date: 2018
- Subjects: Internet of Things , WSN virtualization , Overlay WSN
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278612 , uj:29901 , Citation: Nkomo, M. et al. 2018. Overlay virtualized wireless sensor networks for application in industrial internet of things : a review.
- Description: Abstract: In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field.
- Full Text:
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