Implementing database operations using SIMD instructions
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Incognito: efficient full-domain K-anonymity
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Cost-Based Oracle Fundamentals (Expert's Voice in Oracle)
Cost-Based Oracle Fundamentals (Expert's Voice in Oracle)
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In the era of the Internet, more and more privacy-sensitive data is published online. Even though this kind of data are published with sensitive attributes such as name and social security number removed, the privacy can be revealed by joining those data with some other external data. This technique is called joining attack. Among many techniques developed against the joining attack, the k-anonymization generalizes and/or suppresses some portions of the released microdata so that no individual can be uniquely distinguished from a group of size k. Incognito is one of the most efficient k-anonymization algorithms. However, Incognito requires many repeating sorts against large volume data. In this paper, we propose a bitmap based Incognito algorithm. Using the bitmap technique, we can completely eliminate the expensive sort operations, and can even prune some steps in the traditional Incognito algorithm. Therefore, our new algorithm can improve the performance by an order of magnitude. From the perspective of implementation, the key issue in bitmap based Incognito is the speed of bitwise AND/OR and bit-count operations. For this, we designed and implemented a bitmap package which exploits the Single Instruction Multiple Data technique. Our experimental result shows that bitmap-based Incognito outperforms the traditional Incognito by an order of magnitude.