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Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks

The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security).
- Vrije Universiteit Brussel Belgium
- Department of Computer Science University of Oxford United Kingdom
- Griffith University Australia
- University of Oxford United Kingdom
- Department of Computer Science University of Oxford United Kingdom
Technology, Energy & Fuels, 330, data aggregation, Smart grid, security, Billing, privacy, Engineering, billing, Smart metering network, smart grid, Science & Technology, T, 004, Data aggregation, Physical sciences, smart metering network
Technology, Energy & Fuels, 330, data aggregation, Smart grid, security, Billing, privacy, Engineering, billing, Smart metering network, smart grid, Science & Technology, T, 004, Data aggregation, Physical sciences, smart metering network
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).15 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
