Abstract
The rapid development in current information explosion has led to huge growth in data over time. Increase in internet and communication technology has resulted into generation of data streams. Due to its dynamic nature, the traditional techniques are not sufficient for privacy preservation of data streams. Researchers have been exploring alternative algorithms to achieve improved privacy of data streams. This paper proposes a novel approach to achieve reliable privacy preservation along with an efficient method for reverse engineering. The hashing based privacy preservation proposed in this paper optimizes the use of memory, reduces response time and shows high privacy level. Further the classification of the secured data obtained from this technique has also been analysed for the future behaviour of the data stream using appropriate tools.
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Nyati, A., Dargar, S.K., Sharda, S. (2018). Design and Implementation of a New Model for Privacy Preserving Classification of Data Streams. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_45
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DOI: https://doi.org/10.1007/978-981-13-1813-9_45
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