Ng Wee Keong

Work place: School of Computer Science and Engineering, Nanyang Technological University, Singapore

E-mail: awkng@ntu.edu.sg

Website:

Research Interests: Computer Architecture and Organization, Data Mining, Information Storage Systems, Data Structures and Algorithms, Big data and learning analytics

Biography

Dr. Wee Keong Ng is Associate Professor in the School of Computer Science & Engineering, Nanyang Technological University, Singapore.  He received his Ph.D. from the University of Michigan at Ann Arbor, USA.  His research areas are secure data analytics, secure data storage, data monetization, and data security, and has published more than 200 technical papers in these areas. Dr. Ng has served in program/organizing committees of international conferences. In recent years, he is General Co-chair of the International Conference on Information and Communications Security 2016; Jury Member of the Second Dutch Cyber Security Research Award in March 2016; Senior PC Member of the 20th, 19th, 18th, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining.  Dr. Ng has advised and graduated more than 20 Ph.D. students and 20 Master students.

Author Articles
Multi-dimensional Range Query on Outsourced Database with Strong Privacy Guarantee

By Do Hoang Giang Ng Wee Keong

DOI: https://doi.org/10.5815/ijcnis.2017.10.02, Pub. Date: 8 Oct. 2017

Cloud services have provided important solutions for drastically reducing the cost of data management and maintenance. However, data outsourcing not only deprives clients of direct control over their data but also allows the server to gain direct access to the client data. Data encryption has been recognized as the solution to the privacy issue, but it also creates new challenges for both industry and academia. A naive question is whether the client still has the capability to query and obtain useful information when the data are encrypted and stored remotely. This paper investigates a solution to one of the most important types of query operations over encrypted data, namely multi-dimensional range queries. Our solution combines cryptographic techniques with the bucketization approach. We leverage a three-party architecture and secure multiparty computation to design and analyze the security of the protocols. Further, we discuss solutions for both static and dynamic datasets where new data records can be appended. First, we present the solutions for the case when the set of attributes in the query is pre-defined. Subsequently, we discuss the generalization.

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