Feddp: A privacy-protecting theft detection scheme in smart grids using federated learning
In smart grids (SGs), the systematic utilization of consumer energy data while maintaining its
privacy is of paramount importance. This research addresses this problem by energy theft …
privacy is of paramount importance. This research addresses this problem by energy theft …
Privacy-aware split learning based energy theft detection for smart grids
Energy thefts are one of the critical attacks that often cause high revenue losses for utility
companies around the world. Effective detection of such attacks is very important and must …
companies around the world. Effective detection of such attacks is very important and must …
FedDetect: A novel privacy-preserving federated learning framework for energy theft detection in smart grid
In smart grids, a major challenge is how to effectively utilize consumers' energy consumption
data while preserving security and privacy. In this article, we tackle this challenging issue …
data while preserving security and privacy. In this article, we tackle this challenging issue …
Privacy-preserving and efficient decentralized federated learning-based energy theft detector
Energy theft causes economic losses and power out-ages and disrupts energy generation
and distribution of smart grids. A significant challenge is how to effectively use customers' …
and distribution of smart grids. A significant challenge is how to effectively use customers' …
[HTML][HTML] Step towards secure and reliable smart grids in Industry 5.0: A federated learning assisted hybrid deep learning model for electricity theft detection using smart …
Abstract The integration of Smart Grid technology and conceptual Industry 5.0 has paved the
way for advanced energy management systems that enhance efficiency and revolutionized …
way for advanced energy management systems that enhance efficiency and revolutionized …
p2Detect: Electricity Theft Detection With Privacy Preservation for Both Data and Model in Smart Grid
Electricity Theft Detection (ETD) based on deep learning can detect abnormal electricity
consumption behaviors by analyzing user historical data. However, existing ETD schemes …
consumption behaviors by analyzing user historical data. However, existing ETD schemes …
Decentralized Privacy-Preserving Electricity Theft Detection for Distribution System Operators
Distribution system operators (DSO) may benefit from sharing key information to detect
electricity theft with data-driven methods. However, the privacy of electricity consumers must …
electricity theft with data-driven methods. However, the privacy of electricity consumers must …
Deep active learning-enabled cost-effective electricity theft detection in smart grids
In industrial informatics-enabled smart grids, machine learning approaches have exhibited
high potential in data-driven electricity theft detection (ETD), whereas none of the existing …
high potential in data-driven electricity theft detection (ETD), whereas none of the existing …
Towards sustainable energy efficiency with intelligent electricity theft detection in smart grids emphasising enhanced neural networks
In smart grids, electricity theft is the most significant challenge. It cannot be identified easily
since existing methods are dependent on specific devices. Also, the methods lack in …
since existing methods are dependent on specific devices. Also, the methods lack in …
Ensemble-Learning-based decision support system for energy-theft detection in smart-grid environment
F Mohammad, K Saleem, J Al-Muhtadi - Energies, 2023 - mdpi.com
Theft of electricity poses a significant risk to the public and is the most costly non-technical
loss for an electrical supplier. In addition to affecting the quality of the energy supply and the …
loss for an electrical supplier. In addition to affecting the quality of the energy supply and the …