| Title | Trustworthiness in Sensor Networks A Reputation-Based Method for Weather Stations |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Figueiredo, N. M., Rodríguez, M. C. |
| Conference Name | 2020 International Conference on Omni-layer Intelligent Systems (COINS) |
| Keywords | autonomous sensors, composability, Correlation, correlation theory, data integrity, data mining, Gaussian overlap, Gaussian processes, geophysics computing, Indexes, IoT, Meteorology, Meteorology Data, Pearson correlation, peer-data trust, Peer-to-peer computing, pubcrawl, reputation, reputation indicators, reputation-based method, security of data, self-data trust, sensor fusion, Sensor networks, soft-security feature, Temperature measurement, Time series analysis, Trusted Computing, trustworthiness, trustworthiness approach, weather stations |
| Abstract | Trustworthiness is a soft-security feature that evaluates the correct behavior of nodes in a network. More specifically, this feature tries to answer the following question: how much should we trust in a certain node? To determine the trustworthiness of a node, our approach focuses on two reputation indicators: the self-data trust, which evaluates the data generated by the node itself taking into account its historical data; and the peer-data trust, which utilizes the nearest nodes' data. In this paper, we show how these two indicators can be calculated using the Gaussian Overlap and Pearson correlation. This paper includes a validation of our trustworthiness approach using real data from unofficial and official weather stations in Portugal. This is a representative scenario of the current situation in many other areas, with different entities providing different kinds of data using autonomous sensors in a continuous way over the networks. |
| DOI | 10.1109/COINS49042.2020.9191382 |
| Citation Key | figueiredo_trustworthiness_2020 |
Trustworthiness in Sensor Networks A Reputation-Based Method for Weather Stations