The Smart Grid aims to enhance the electric grid’s reliability, safety, and efficiency by utilizi... more The Smart Grid aims to enhance the electric grid’s reliability, safety, and efficiency by utilizing digital information and control technologies. Real-time analysis and state estimation methods are crucial for ensuring proper control implementation. However, the reliance of Smart Grid systems on communication networks makes them vulnerable to cyberattacks, posing a significant risk to grid reliability. To mitigate such threats, efficient intrusion detection and prevention systems are essential. This paper proposes a hybrid deep-learning approach to detect distributed denial-of-service attacks on the Smart Grid’s communication infrastructure. Our method combines the convolutional neural network and recurrent gated unit algorithms. Two datasets were employed: The Intrusion Detection System dataset from the Canadian Institute for Cybersecurity and a custom dataset generated using the Omnet++ simulator. We also developed a real-time monitoring Kafka-based dashboard to facilitate attack ...
Abstract: Participation in social networking sites has dramatically increased in recent years. So... more Abstract: Participation in social networking sites has dramatically increased in recent years. Social networking sites like Facebook1 or MySpace allow users to keep in touch with their friends, communicate and share content, ideas, activities, recommendations, with them, as well as engage in other multiuser applications. Services allow millions of individuals to create online profile and share personal information with vast networks of friends and often, unknown numbers of strangers. There are potential attacks on various aspects of user privacy. It is not well understood how privacy concern and trust influence social interactions within social networking sites. The continuous number of high-profile Internet security breaches reported in the mass media shows that despite an emphasis on security processes that there is still a gap between theory and practice. I intend in this research paper to propose a new model base on suggested model on social networking analysis and suggest a new...
Mining sector is an important sector that contributes to regional development therefore, it has t... more Mining sector is an important sector that contributes to regional development therefore, it has to be managed sustainably. This became basis of this study. Problem examined was comparative advantage of mining toward South Sulawesi. This study used multidimensional scaling and input-output analysis. Those analyses used input-output table data of 2010 in classification of 11 economic sectors and GDRP of 24 districts/cities of South Sulawesi in 2012-2016 which was obtained from BPS (Central Bureau of Statistics) South Sulawesi. Results showed that final value of the mining sector in South Sulawesi was Rp9,007,814,000,000, describing role of mining sector as relatively small compared to other sectors. Shift share described economic growth of mining sector in Luwu Timur was faster than other districts. Export base (LQ) and shift share ere indicators that showed that Luwu Timur was superior to other districts. LQ value from Luwu Timur was 9.39 indicating that mining sector was self-suffi...
International Journal of Scientific & Technology Research, 2014
Participation in social networking sites has dramatically increased in recent years. Social netwo... more Participation in social networking sites has dramatically increased in recent years. Social networking sites like Facebook1 or MySpace allow users to keep in touch with their friends, communicate and share content, ideas, activities, recommendations, with them, as well as engage in other multiuser applications. Services allow millions of individuals to create online profile and share personal information with vast networks of friends and often, unknown numbers of strangers. There are potential attacks on various aspects of user privacy. It is not well understood how privacy concern and trust influence social interactions within social networking sites. The continuous number of high-profile Internet security breaches reported in the mass media shows that despite an emphasis on security processes that there is still a gap between theory and practice. I intend in this research paper to propose a new model base on suggested model on social networking analysis and suggest a new security ...
The critical challenge of enhancing the resilience and sustainability of energy management system... more The critical challenge of enhancing the resilience and sustainability of energy management systems has arisen due to historical outages. A potentially effective strategy for addressing outages in energy grids involves preparing for future failures resulting from line vulnerability or grid disruptions. As a result, many researchers have undertaken investigations to develop machine learning-based methodologies for outage forecasting for smart grids. This research paper proposed applying ensemble methods to forecast the conditions of smart grid devices during extreme weather events to enhance the resilience of energy grids. In this study, we evaluate the efficacy of five machine learning algorithms, namely support vector machines (SVM), artificial neural networks (ANN), logistic regression (LR), decision tree (DT), and Naive Bayes (NB), by utilizing the bagging ensemble technique. The results demonstrate a remarkable accuracy rate of 99.98%, with a true positive rate of 99.6% and a fal...
The Smart Grid aims to enhance the electric grid’s reliability, safety, and efficiency by utilizi... more The Smart Grid aims to enhance the electric grid’s reliability, safety, and efficiency by utilizing digital information and control technologies. Real-time analysis and state estimation methods are crucial for ensuring proper control implementation. However, the reliance of Smart Grid systems on communication networks makes them vulnerable to cyberattacks, posing a significant risk to grid reliability. To mitigate such threats, efficient intrusion detection and prevention systems are essential. This paper proposes a hybrid deep-learning approach to detect distributed denial-of-service attacks on the Smart Grid’s communication infrastructure. Our method combines the convolutional neural network and recurrent gated unit algorithms. Two datasets were employed: The Intrusion Detection System dataset from the Canadian Institute for Cybersecurity and a custom dataset generated using the Omnet++ simulator. We also developed a real-time monitoring Kafka-based dashboard to facilitate attack ...
Abstract: Participation in social networking sites has dramatically increased in recent years. So... more Abstract: Participation in social networking sites has dramatically increased in recent years. Social networking sites like Facebook1 or MySpace allow users to keep in touch with their friends, communicate and share content, ideas, activities, recommendations, with them, as well as engage in other multiuser applications. Services allow millions of individuals to create online profile and share personal information with vast networks of friends and often, unknown numbers of strangers. There are potential attacks on various aspects of user privacy. It is not well understood how privacy concern and trust influence social interactions within social networking sites. The continuous number of high-profile Internet security breaches reported in the mass media shows that despite an emphasis on security processes that there is still a gap between theory and practice. I intend in this research paper to propose a new model base on suggested model on social networking analysis and suggest a new...
Mining sector is an important sector that contributes to regional development therefore, it has t... more Mining sector is an important sector that contributes to regional development therefore, it has to be managed sustainably. This became basis of this study. Problem examined was comparative advantage of mining toward South Sulawesi. This study used multidimensional scaling and input-output analysis. Those analyses used input-output table data of 2010 in classification of 11 economic sectors and GDRP of 24 districts/cities of South Sulawesi in 2012-2016 which was obtained from BPS (Central Bureau of Statistics) South Sulawesi. Results showed that final value of the mining sector in South Sulawesi was Rp9,007,814,000,000, describing role of mining sector as relatively small compared to other sectors. Shift share described economic growth of mining sector in Luwu Timur was faster than other districts. Export base (LQ) and shift share ere indicators that showed that Luwu Timur was superior to other districts. LQ value from Luwu Timur was 9.39 indicating that mining sector was self-suffi...
International Journal of Scientific & Technology Research, 2014
Participation in social networking sites has dramatically increased in recent years. Social netwo... more Participation in social networking sites has dramatically increased in recent years. Social networking sites like Facebook1 or MySpace allow users to keep in touch with their friends, communicate and share content, ideas, activities, recommendations, with them, as well as engage in other multiuser applications. Services allow millions of individuals to create online profile and share personal information with vast networks of friends and often, unknown numbers of strangers. There are potential attacks on various aspects of user privacy. It is not well understood how privacy concern and trust influence social interactions within social networking sites. The continuous number of high-profile Internet security breaches reported in the mass media shows that despite an emphasis on security processes that there is still a gap between theory and practice. I intend in this research paper to propose a new model base on suggested model on social networking analysis and suggest a new security ...
The critical challenge of enhancing the resilience and sustainability of energy management system... more The critical challenge of enhancing the resilience and sustainability of energy management systems has arisen due to historical outages. A potentially effective strategy for addressing outages in energy grids involves preparing for future failures resulting from line vulnerability or grid disruptions. As a result, many researchers have undertaken investigations to develop machine learning-based methodologies for outage forecasting for smart grids. This research paper proposed applying ensemble methods to forecast the conditions of smart grid devices during extreme weather events to enhance the resilience of energy grids. In this study, we evaluate the efficacy of five machine learning algorithms, namely support vector machines (SVM), artificial neural networks (ANN), logistic regression (LR), decision tree (DT), and Naive Bayes (NB), by utilizing the bagging ensemble technique. The results demonstrate a remarkable accuracy rate of 99.98%, with a true positive rate of 99.6% and a fal...
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Papers by Ulaa Alhaddad