SMART METER DATA ANALYSIS AND SECURITY ISSUES/SOLUTIONS BY USING MACHINE LEARNING
| dc.contributor.author | KHADIJA AMEEN | |
| dc.date.accessioned | 2025-12-17T11:45:43Z | |
| dc.date.available | 2025-12-17T11:45:43Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Smart metering systems are being implemented to improve grid reliability and energy efficiency whereas also improving customer service. Smart meters are gradually replacing traditional energy meters due to their numerous advantages, including faster two-way communication between electricity providers and end-users, enabling direct load control for demand response, energy savings, and so on. Fraudulent consumers, on the other hand, commit electricity theft and a variety of other cyber-attacks by modifying and reporting fake readings in order to reduce their bills illegally. Because the readings are used for grid management, these attacks not only inflict financial losses, but they also have the potential to degrade the system's functioning. In this study, a review of smart meter’s data analysis techniques and security issues was presented. Afterward, a structured overview and recommendations of security solutions via machine learning techniques were provided that are needed for security of smart meter’s data delivery and management. | |
| dc.identifier.uri | https://escholar.umt.edu.pk/handle/123456789/16608 | |
| dc.language.iso | en | |
| dc.publisher | UMT Lahore | |
| dc.title | SMART METER DATA ANALYSIS AND SECURITY ISSUES/SOLUTIONS BY USING MACHINE LEARNING | |
| dc.type | Thesis |
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