Hong Kong Baptist University (HKBU) Research Cluster on Data Analytics and Artificial Intelligence in X

Verifiable Publish/Subscribe Queries over Outsourced Data Streams
Principal Investigatgor: Prof. Jianliang XU ( Department of Computer Science )

Today’s data streaming platforms, such as Twitter, Facebook, and Bitcoin, continuously generate a massive amount of data at an unprecedented scale. For example, over 500 million tweets are posted on Twitter each day and over 200,000 transactions are managed by Bitcoin each day. Building publish/subscribe systems for these platforms that allow subscribers to filter relevant data objects has many real-world applications. For example, Twitter users may want to be updated with tweets on a specific event (e.g., flu outbreak); Bitcoin users may want to be kept abreast of transactions issued by specific parties (e.g., angel investors). To support millions of subscription queries, outsourcing publish/subscribe query processing to a third-party cloud has been deemed a desirable solution to scaling up systems. However, the outsourcing of query processing naturally raises the issue of trust, making it indispensable for subscribers to verify the results returned by the cloud. In this project, we take a first step to comprehensively investigate the problem of authenticating publish/subscribe queries regarding outsourced data streams.


  • To design novel security primitives and query authentication algorithms for the verification of Boolean-based publish/subscribe queries over outsourced data streams;
  • To propose space partition-based query indexing techniques for the handling of large-scale subscription queries;
  • To extend the proposed solutions to top-k publish/subscribe queries and historical time-window queries;
  • To evaluate the proposed techniques by combining theoretical analysis and empirical experiments.

Grant Support:

This project is supported by the Research Grants Council (RGC), Hong Kong SAR, China (Project 12201018).

For further information on this research topic, please contact Prof. Jianliang XU.