Verifiable and Privacy-preserving Query in IoT-Cloud DataStreaming
| Autor: | I-Chen Tsai, 蔡宜蓁 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 As IoT devices are becoming part of our everyday life and some of these devices have access to sensitive data that we don’t want any malicious party to make use of, we should pay more attention on their security issues. Since IoT devices are often resource-constrained, data need to be outsourced to cloud storages. However, cloud storages are consider honest-but-curious, which means they may try to know what the data is about or return a falsified answer when the client requests a query operation. Under this scenario, we try to solve the problem of performing verifiable privacy-preserving queries under streaming settings. In this thesis, we proposed two data structures, HPBTree (for range query) and MIXBtree (for top-k query) to solve the problem. With these data structures, cloud storage providers can perform secure range or top-k query. Moreover, user can verify the correctness of the query results and check the freshness of his outsourced data. In this way, cloud storage providers can contribute more functionalities based on the most used SQL queries and user can make sure their data is under protected at the same time. We evaluate our proposed methods and demonstrate that our construction is efficient and practical. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|