VENUS: Verifiable range query in data streaming
Ichen Tsai, Chia-Mu Yu, Haruo Yokota, Sy‐Yen Kuo · 2018
Internet of Things (IoT) devices have gained the popularity in our daily life. As IoT devices are usually resource-constrained, the sensed data cannot be kept in the local memory and need to be outsourced to the cloud in a streaming manner. However, the untrusted cloud might return the falsified answer to the query made by the user. Verifiable data outsourcing addresses the similar problem, but the design challenge here mainly comes with the fact that the user can only have the vision on a single data at any time slot. In this paper, we propose VENUS to achieve verifiable range query in data streaming. In particular, VENUS ensures data confidentiality and query answer integrity of the range query in the data streaming, by taking advantage of our proposed flexible and authenticated data structure HPBTree. The simulation and analytical results demonstrate the efficiency and effectiveness of VENUS.