Efficient and Privacy Preserving Clustering Algorithm for Spatiotemporal Data

Abid Mehmood, Iynkaran Natgunanathan and Yong Xiang
Additional contact information
Abid Mehmood: College of Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates
Iynkaran Natgunanathan: School of Information Technology, Deakin University, Burwood, VIC, Australia
Yong Xiang: School of Information Technology, Deakin University, Burwood, VIC, Australia

International Journal of Information Technology & Decision Making (IJITDM), 2024, vol. 23, issue 02, 967-992

Abstract: The efficiency of a spatiotemporal data analysis algorithm decreases as the amount of data increases. Many clustering techniques have been proposed for data analysis applications. However, applying those techniques to spatiotemporal data clustering is still in its infancy. In this paper, we tackle the issue of clustering spatiotemporal data on public Cloud based on the distance between them. To increase the efficiency of spatiotemporal clustering, we have proposed a MapReduce-based framework for clustering. However, as spatiotemporal dataset contains sensitive information, directly outsourcing spatiotemporal data to Cloud servers will raise privacy concerns. To address the problem of privacy, we have proposed a privacy preserving clustering algorithm based on MapReduce for spatiotemporal data that can be efficiently outsourced for data processing on the Cloud servers. The proposed scheme allows the clustering operation to be performed directly on the encrypted spatiotemporal data by Cloud server. Extensive experimental evaluation with trajectory data shows that our scheme efficiently produces higher quality clustering results.

Keywords: Clustering; privacy protection; spatiotemporal data (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622022500110
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:23:y:2024:i:02:n:s0219622022500110

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622022500110

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().