Secure and Privacy Driven Energy Data Analytics
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- PhD theses (TN-IDE) 
Original versionSecure and Privacy Driven Energy Data Analytics by Dhanya Therese Jose, Stavanger : University of Stavanger, 2022 (PhD thesis UiS, no. 673)
Renewable resources are the main energy sources in a smart grid project. In order to ensure the smooth functioning of the smart grid, Information and Communication Technologies (ICT) need to be utilised efficiently. The objective of the SmartNEM project is to effectively utilise the technologies such as Machine Learning, Blockchain and Data Hubs for the aforementioned purpose and at the same time ensure a secured and privacy preserved solution. The data involved in smart grids require high security and it can be sensitive due to the household data which contains personal information. The individuals can be reluctant to share these data due to mistrust and to avoid unnecessary manipulation of the data they provide. In order to overcome this it is necessary to build a trust based framework in which one could ensure data security and data privacy for the data owners to open up their data for data analysis. To achieves this we have proposed an architecture called TOTEM, Token for Controlled Computation, which integrates Blockchain and Big Data technologies. The conventional method of data analysis demands data be moved across the network to the location where the execution happens, however in the TOTEM architecture computational code will be moved to the data owner’s environment where the data is located. The TOTEM is a three layer architecture (Blockchain consortium layer, Storage layer and Computational layer) with two main actors, data provider and data consumer. Data provider provides metadata of the data they own and provide resources for the execution of data. Data consumers will get an opportunity to execute their own code on the data provider´s data. For a controlled computation and to avoid malicious functions an entity called totem is introduced in the architecture. The authorised users should meet the requirements of Totem value for executing their code on the requested data. For live monitoring of the totem value throughout the run time is achieved with the components such as totem manager and updaters in the computational layer. The code must follow a specific format and will undergo preliminary checks with the TOTEM defined SDK and smart contracts deployed by the data providers in the blockchain network. The Extended TOTEM architecture is also proposed to address the additional features when it is needed to combine the results from multiple data providers without sharing the data. This research work focused on the design of the TOTEM architecture and implementation as a proof of concept for the newly introduced components in the architecture. We have also introduced artificial intelligence in the framework to improve core features’ functionality. In the present research, the TOTEM architecture is proposed for the SmartNEM project to utilize the energy data for decision making and figure out the trends or patterns, while maintaining data privacy, data ownership, accountability and traceability. Moreover, the architecture can be extended to other domains such as health, education, etc, where data security and privacy is the key concern in sharing the data.
PhD thesis in Information technology
Has partsPaper 1: TOTEM : Jose, D.T., Chakravorty, A., Rong, C. (2019) Token for controlled computation. Integrating Blockchain with Big Data. Proceedings of 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India
Paper 2: Jose, D.T., Chakravorty, A., Rong, C. (2020) Distributed computational framework in TOTEM architecture enabled by blockchain. Proceedings of 15th International Conference on Computer Science & Education (ICCSE), Delft, Netherlands
Paper 3: Behzad, B., Jose, D.T., Chakravorty, A., Rong, C. (2021) TOTEM SDK: an open toolset for token controlled computation managed by blockchain. Proceedings of 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Brisbane, Australia
Paper 4: Jose, D.T., Holme, J., Chakravorty, A., Rong, C. (2022) Integrating big data and blockchain to manage energy smart grids—TOTEM framework. Blockchain: Research and Applications, 3(3). DOI: 10.1016/j.bcra.2022.100081
Paper 5: Jose, D.T., Rong, C., Chakravorty, A. (2022) Application of Artificial intelligence in secure decentralised computation enabled by TOTEM. Accepted for publication.
PublisherUniversity of Stavanger, Norway
SeriesPhD thesis UiS;