Privacy protection on sliding window of data streams

—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.

• Type: Conference
• Year: 2007
• Where: COLCOM
• Authors: Weiping Wang 0001, Jianzhong Li, Chunyu Ai, Yingshu Li
• Keywords: COLCOM 2007, Data Streams, Sliding Window, Transaction Data