Abstract
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.
This research was supported in part by MIC, Korea under ITRC IITA-2006-(C1090-0603-0046), in part by MIC & IITA through IT Leading R&D Support Project.
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© 2007 Springer-Verlag Berlin Heidelberg
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Kang, HH., Kim, JM., Na, GJ., Lee, SW. (2007). Implementation of Bitmap Based Incognito and Performance Evaluation. In: Kotagiri, R., Krishna, P.R., Mohania, M., Nantajeewarawat, E. (eds) Advances in Databases: Concepts, Systems and Applications. DASFAA 2007. Lecture Notes in Computer Science, vol 4443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71703-4_39
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DOI: https://doi.org/10.1007/978-3-540-71703-4_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71702-7
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