Abstract
Privacy preserving mining of distributed data has numerous applications. Several constraints can imposed by the applications, it includes how the data is distributed; when the data is distributed privacy should be preserved...etc. Data mining has operated on a data warehousing model of gathering all data into a central site, then running an algorithm against that data. Privacy considerations may prevent this approach. This paper presents steganography techniques and shows how they can be used to solve several privacy-preserving data mining problems. Steganography is a technique to hide secret information in some other data (we call it a vessel) without leaving any apparent evidence of data alteration.
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Aruna Kumari, D., Raja Sekhar Rao, K., Suman, M. (2010). Privacy Preserving Mining of Distributed Data Using Steganography. In: Meghanathan, N., Boumerdassi, S., Chaki, N., Nagamalai, D. (eds) Recent Trends in Network Security and Applications. CNSA 2010. Communications in Computer and Information Science, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14478-3_27
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DOI: https://doi.org/10.1007/978-3-642-14478-3_27
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