Thesis Topic Details

Topic ID:
3409
Title:
Privacy-Aware Smart-Grid Monitoring
Supervisor:
Guillaume Jourjon
Research Area:
Networks, Distributed Systems
Associated Staff
Assessor:
Salil Kanhere
Topic Details
Status:
Active
Type:
R & D
Programs:
CS
Group Suitable:
Industrial:
Pre-requisites:
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Description:
Advancements in sensing, actuation, and networking technologies is speeding-up the development of smart electrical grids. Smart grids aim to reduce overall energy consumption via accurate monitoring of buildings, controlling/managing electricity demand, and incorporating renewable energy sources in the supply chain. In this context, it is envisioned that several sensors (e.g. temperature, real-time energy consumptions) would communicate in order to both optimize the needed electricity production as well as its distribution.

While the smart-grid initiative is foreseen as a needed means to reduce the carbon footprint of humankind, it also raises ethical questions about the continuous monitoring of people activities. Indeed, collecting people premises information would allow inferring owner's behaviour and life style without their consent.

In this honours project the student will adapt and develop new privacy preserving algorithms to support privacy preserving smart grid applications. To this end, the student will leverage the OML measurement framework, a middleware that supports data collection from distributed sources, and allows to integrate data filtering in the collection process. Such filters would enable privacy protection through input perturbation, allowing straightforward implementation of privacy preserving data collection. For applications that require access to accurate aggregates, this framework can easily support techniques like those proposed in the literature, where intermediate inputs are perturbed to protect privacy, while ensuring that over longer time periods the overall noise elements cancel each other out. Furthermore, a similar approach can be adapted to allow accurate analysis over aggregates (e.g., neighbourhoods) at a single point in time, while ensuring privacy for any subset of buildings, or to leverage both spatial and
temporal dimensions when determining aggregation levels.

During this honours project, the student will be included in small but very dynamic team of researchers in which they will have a large freedom to propose new measurement schemes (e.g. filtering) as well as new monitoring applications.
A more detailed roadmap of this honours project is as follows:
1. Literature review of network measurement architectures and privacy preserving solutions.
2. Design/modification of the existing measurement architecture. This includes the dynamic
combination of measurement streams in and between smart meters.
3. Development of the privacy preserving filtering capabilities.
4. Implementation of the basic features of the monitoring architecture.
5. Performance evaluation in the mock-up scenario consisting of neighborhood size network.
Comments:
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Past Student Reports
 
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