Verifiable Data Streaming Protocol Supporting Keyword Queries

The rapid deployment of emerging networks, such as the Internet of Things and cloud computing, has generated massive amounts of data. Data streaming is significant among these various data types due to its widespread use in many critical applications, such as gene sequencing, network intrusion detection, and stock trading. On the other hand, the continuously increased size of data streaming makes it impractical to store and manage the data locally, especially for those resource-constrained devices. Outsourcing the data streaming to cloud servers provides an ideal solution to the above storage issue. However, this raises the problem of how to guarantee the integrity of the outsourced data, as cloud servers may maliciously modify the data. To this end, the primitive of verifiable data streaming (VDS) was introduced to preserve the integrity of the outsourced data streaming, enabling data users to ensure that queried data items, including the contents and corresponding positions, are correct. Despite many proposed VDS protocols, most can only use the position index to query outsourced data streaming. Consequently, they fail to fulfill the requirements of those practical applications that need keyword queries. For example, in the setting of network intrusion detection, the data analyst would like to query all access records from the same IP address. In this paper, we extend the original VDS protocol to support keyword queries, i.e., allowing data users to retrieve outsourced data items with particular keywords. Specifically, we use a prefix tree to maintain keywords and another chameleon authentication tree to store data items. The two trees are bound together with cryptographic query proofs, ensuring the consistency between the position index and keyword queries. The proposed VDS protocol, which supports keyword queries, is proven secure in the standard model and outperforms previous VDS protocols in terms of functionality. The experimental results indicate that our proposal is also efficient and practical.

• Publication year

  2026

• Venue

  IEEE Transactions on Network and Service Management

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1109/TNSM.2025.3629071
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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