2022 Fiscal Year Research-status Report
Blockchain-empowered Contact Tracing for COVID-19 Using Crypto-spatiotemporal Information
| Project/Area Number |
21K17737
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| Research Institution | Waseda University |
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Principal Investigator |
文 鄭 早稲田大学, 理工学術院, 講師(任期付) (70822261)
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| Project Period (FY) |
2021-04-01 – 2026-03-31
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| Keywords | Spatiotemporal info / Blockchain / TEE / IoT / GNSS Spoofing |
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| Outline of Annual Research Achievements |
This year, our research focused on enhancing the trustworthiness of spatio-temporal data and refining authentication technologies. We addressed the security shortcomings of civilian Global Navigation Satellite System (GNSS) devices by conducting GNSS spoofing experiments. Our analyses led to innovative strategies that could assist devices in identifying GNSS spoofing and acquiring precise spatio-temporal data.
Simultaneously, we made advancements in spatio-temporal information authentication. Recognizing the importance of secure and accurate geolocation data, we explored new approaches for its validation. We incorporated cryptographic techniques, secure transmission protocols, and TEE solutions to augment the reliability and trustworthiness of spatio-temporal data.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Research Progress: The research is progressing smoothly. We have conducted multiple experiments, tested numerous devices, and gathered a substantial amount of data. This extensive experimental process has allowed us to obtain a comprehensive understanding of the problem at hand, and we have made significant headway towards developing effective solutions for the same. As we continue to analyze the collected data and refine our methodologies, we expect further advancements in the near future.
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| Strategy for Future Research Activity |
For future research, we plan to delve deeper into the area: leveraging artificial intelligence (AI) to detect GNSS attacks on terminal devices
AI has shown great potential in identifying patterns and anomalies that might be indicative of GNSS attacks. We aim to design and implement AI-driven models that can accurately and efficiently detect and mitigate these attacks. Our goal is to enhance the resilience of GNSS devices against spoofing and other forms of attacks, ensuring the integrity of spatio-temporal data and the overall safety of navigation systems.
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| Causes of Carryover |
The reduction in international conferences, coupled with access to numerous complimentary experimental facilities and resources, has significantly saved on our budget. This has allowed us to redirect funds towards other areas of our research, enhancing our capabilities and accelerating our progress.
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Research Products
(14 results)
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[Presentation] GNSS Spoofing Detection using Multiple Sensing Devices and Decision Tree Classifier.2022
Author(s)
Qi, X., Sato, T., Wen, Z., Takeuchi, M., Katsuyama, Y., Tamesue, K., ... & Sato, T.
Organizer
International Conference on Emerging Technologies for Communications
Int'l Joint Research
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