With the widespread development of intelligent systems, a considerable number of mobile devices are connected together, and continuously generate huge amounts of data. Although cloud storage provides perfect solution for effectively storing these massive data, how to ensure the integrity of the outsourced data becomes challenging. For this reason, the primitive of verifiable data streaming (VDS) protocol was introduced, and enables a data owner to continuously outsource streaming data to an untrusted cloud server, while capturing the integrity of the outsourced data. That is, when a data user retrieves some data item via its index from the server, he/she can publicly verify its integrity with the proof generated and returned by the server. Supporting data update is one of the major features of VDS, and allows the data owner to replace an old data item with a new one. Although many VDS protocols have been proposed to enhance the functionality and efficiency of the original VDS protocol, they all ignore the issue of preserving those updated data items. In fact, in various application scenarios of VDS, preserving and storing previously updated data items is actually necessary. For example, in the setting of DNA sequencing, there might be multiple versions of DNA fragments at the same location due to the genetic mutation. Obviously, for more precise treatment, all these DNA fragments need to be preserved. To this end, in this paper, we propose a VDS protocol that features of enabling the query of the update history of each data item. Specifically, we first put forward a new chameleon authentication tree with update history (UCAT), which consists of two CATs (the basic tree and the update history tree). In more detail, the basic tree is used to store the data item appended to the corresponding location for the first time, and the update history tree is utilized to preserve each updated version of the corresponding data item. Furthermore, based on UCAT, we propose a VDS protocol supporting update history queries, which allows a data user to retrieve any version of the data item. The theoretical analysis and performance evaluation indicate that our protocol outperforms previous ones in the field of functionality, and its computation/communication costs are acceptable. We also prove its security in the standard model.

The wide deployment of Internet of Things (IoT) devices enables the controller to continuously collect massive volume data in automation systems, and makes it possible to make intelligent decisions based on machine learning techniques. In fact, data-driven intelligent automation systems have been common in the industrial community. Nevertheless, how to effectively store the collected stream data and ensure their integrity is still challenging. To this end, the notion of verifiable data streaming (VDS) protocol, which enables a client to outsource the stream data to an untrusted server in a verifiable manner, was introduced. However, we argue that existing VDS protocols based on the chameleon authentication tree (CAT) are inefficient in the data update, since the whole CAT must be updated accordingly to avoid acute exposure of chameleon hashing. Thus, they are infeasible for intelligent automation systems that need to frequently update data. In this article, we first introduce a new primitive called double-trapdoor chameleon hash tree (DCHT) based on the double-trapdoor chameleon hash families, where each leaf of DCHT is calculated and fixed by using a double-trapdoor chameleon hash family, making the entire DCHT always unchanged. Furthermore, we propose a novel VDS protocol based on the DCHT. Due to the distinctive properties of the underlying DCHT, the proposed VDS protocol has a constant update cost and more efficient than previous VDS protocols based on CAT. Besides, we prove that the proposed VDS protocol is secure in the standard model.