On the public citation graph

A Practical and Generalizable Framework for Electricity Theft Detection in Smart Grids

https://doi.org/10.2139/ssrn.5374864
0 signed · 42 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1016/j.apenergy.2019.01.076openalex-snapshot
A practical feature-engineering framework for electricity theft detection in smart grids
inferredcites →https://doi.org/10.1016/j.apenergy.2022.120396openalex-snapshot
Federated fuzzy k-means for privacy-preserving behavior analysis in smart grids
inferredcites →https://doi.org/10.1016/j.apenergy.2023.121734openalex-snapshot
Large-scale monitoring of residential heat pump cycling using smart meter data
inferredcites →https://doi.org/10.1016/j.apenergy.2023.121914openalex-snapshot
Multi-view broad learning system for electricity theft detection
inferredcites →https://doi.org/10.1016/j.apenergy.2023.122157openalex-snapshot
Enhancing anomaly detection accuracy and interpretability in low-quality and class imbalanced data: A comprehensive approach
inferredcites →https://doi.org/10.1016/j.apenergy.2024.122847openalex-snapshot
Multi-Objective Evolutionary Hybrid Deep Learning for energy theft detection
inferredcites →https://doi.org/10.1016/j.apenergy.2024.123228openalex-snapshot
Two-stage generalizable approach for electricity theft detection in new regions
inferredcites →https://doi.org/10.1016/j.apenergy.2024.123545openalex-snapshot
An adaptive privacy protection framework for user energy data using dictionary learning and watermarking techniques
inferredcites →https://doi.org/10.1016/j.apenergy.2024.124789openalex-snapshot
A privacy-preserving heterogeneous federated learning framework with class imbalance learning for electricity theft detection
inferredcites →https://doi.org/10.1016/j.ijepes.2020.106448openalex-snapshot
Electricity theft detection based on stacked sparse denoising autoencoder
inferredcites →https://doi.org/10.1038/s41467-025-59749-4openalex-snapshot
Vulnerability of power distribution networks to local temperature changes induced by global climate change
inferredcites →https://doi.org/10.1103/prxenergy.1.033005openalex-snapshot
Defending Smart Electrical Power Grids against Cyberattacks with Deep Q -Learning
inferredcites →https://doi.org/10.1109/access.2021.3100980openalex-snapshot
Electricity Theft Detection in AMI Based on Clustering and Local Outlier Factor
inferredcites →https://doi.org/10.1109/access.2023.3318111openalex-snapshot
Clustering and Ensemble Based Approach for Securing Electricity Theft Detectors Against Evasion Attacks
inferredcites →https://doi.org/10.1109/i2mtc43012.2020.9128712openalex-snapshot
Electricity Theft Detection Base on Extreme Gradient Boosting in AMI
inferredcites →https://doi.org/10.1109/icdmw53433.2021.00070openalex-snapshot
EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid
inferredcites →https://doi.org/10.1109/tii.2017.2785963openalex-snapshot
Wide and Deep Convolutional Neural Networks for Electricity-Theft Detection to Secure Smart Grids
inferredcites →https://doi.org/10.1109/tii.2018.2873814openalex-snapshot
A Novel Combined Data-Driven Approach for Electricity Theft Detection
inferredcites →https://doi.org/10.1109/tim.2020.3048784openalex-snapshot
Electricity Theft Detection Base on Extreme Gradient Boosting in AMI
inferredcites →https://doi.org/10.1109/tim.2022.3189748openalex-snapshot
A Novel Unsupervised Data-Driven Method for Electricity Theft Detection in AMI Using Observer Meters
inferredcites →https://doi.org/10.1109/tim.2023.3324674openalex-snapshot
Electricity Theft Detection in Incremental Scenario: A Novel Semi-Supervised Approach Based on Hybrid Replay Strategy
inferredcites →https://doi.org/10.1109/tpwrs.2019.2928276openalex-snapshot
Fraud Detection in Electric Power Distribution: An Approach That Maximizes the Economic Return
inferredcites →https://doi.org/10.1109/tpwrs.2021.3125613openalex-snapshot
Solar Panel Identification Via Deep Semi-Supervised Learning and Deep One-Class Classification
inferredcites →https://doi.org/10.1109/tpwrs.2022.3196403openalex-snapshot
Electricity Theft Detection Using Euclidean and Graph Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tpwrs.2023.3262773openalex-snapshot
Enhance Unobservable Solar Generation Estimation via Constructive Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/tpwrs.2023.3314708openalex-snapshot
Distribution Grid Line Outage Identification With Unknown Pattern and Performance Guarantee
inferredcites →https://doi.org/10.1109/tpwrs.2024.3411023openalex-snapshot
Privacy-Preserving Line Outage Detection in Distribution Grids: An Efficient Approach With Uncompromised Performance
inferredcites →https://doi.org/10.1109/tsg.2015.2425222openalex-snapshot
Electricity Theft Detection in AMI Using Customers’ Consumption Patterns
inferredcites →https://doi.org/10.1109/tsg.2019.2892595openalex-snapshot
Energy Theft Detection Using Gradient Boosting Theft Detector With Feature Engineering-Based Preprocessing
inferredcites →https://doi.org/10.1109/tsg.2020.2973681openalex-snapshot
Deep Learning Detection of Electricity Theft Cyber-Attacks in Renewable Distributed Generation
inferredcites →https://doi.org/10.1109/tsg.2020.3047864openalex-snapshot
Robust Electricity Theft Detection Against Data Poisoning Attacks in Smart Grids
inferredcites →https://doi.org/10.1109/tsg.2021.3134018openalex-snapshot
A Stacked Machine and Deep Learning-Based Approach for Analysing Electricity Theft in Smart Grids
inferredcites →https://doi.org/10.1109/tsg.2022.3148817openalex-snapshot
Fraud Detection on Power Grids While Transitioning to Smart Meters by Leveraging Multi-Resolution Consumption Data
inferredcites →https://doi.org/10.1109/tsg.2022.3193989openalex-snapshot
Robust Data-Driven Detection of Electricity Theft Adversarial Evasion Attacks in Smart Grids
inferredcites →https://doi.org/10.1109/tsg.2022.3214194openalex-snapshot
p2Detect: Electricity Theft Detection With Privacy Preservation for Both Data and Model in Smart Grid
inferredcites →https://doi.org/10.1109/tsg.2023.3246459openalex-snapshot
Privacy-Preserving Electricity Theft Detection Based on Blockchain
inferredcites →https://doi.org/10.1109/tsg.2023.3263219openalex-snapshot
Electricity Theft Detection Based on Contrastive Learning and Non-Intrusive Load Monitoring
inferredcites →https://doi.org/10.1109/tsg.2023.3274642openalex-snapshot
FLLF: A Fast-Lightweight Location Detection Framework for False Data Injection Attacks in Smart Grids
inferredcites →https://doi.org/10.1109/tsg.2024.3455368openalex-snapshot
MSDM: Multi-Scale Differencing Modeling for Cross-Scenario Electricity Theft Detection
inferredcites →https://doi.org/10.1109/tsg.2025.3546219openalex-snapshot
Self-Supervised Latent Feature-Guided Multi-Step Diffusion Model for Electricity Theft Detection With Imbalanced and Missing Data
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.