Research Article
Privacy Protection on Sliding Window of Data Streams
@INPROCEEDINGS{10.1109/COLCOM.2007.4553832, author={Weiping Wang and Jianzhong Li and Chunyu Ai and Yingshu Li}, title={Privacy Protection on Sliding Window of Data Streams}, proceedings={3rd International ICST Conference on Collaborative Computing: Networking, Applications and Worksharin}, publisher={IEEE}, proceedings_a={COLLABORATECOM}, year={2008}, month={6}, keywords={Algorithm design and analysis Application software Computer science Data privacy Intelligent systems Joining processes Marketing and sales Monitoring Protection Telephony}, doi={10.1109/COLCOM.2007.4553832} }- Weiping Wang
Jianzhong Li
Chunyu Ai
Yingshu Li
Year: 2008
Privacy Protection on Sliding Window of Data Streams
COLLABORATECOM
IEEE
DOI: 10.1109/COLCOM.2007.4553832
Abstract
In many applications, transaction data arrive in the form of high speed data streams. These data contain a lot of information about customers that needs to be carefully managed to protect customers’ privacy. In this paper, we consider the problem of preserving customer’s privacy on the sliding window of transaction data streams. This problem is challenging because sliding window is updated frequently and rapidly. We propose a novel approach, SWAF (Sliding Window Anonymization Framework), to solve this problem by continuously facilitating kanonymity on the sliding window. Three advantages make SWAF practical: (1) Small processing time for each tuple of data steam. (2) Small memory requirement. (3) Both privacy protection and utility of anonymized sliding window are carefully considered. Theoretical analysis and experimental results show that SWAF is efficient and effective.