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Improved perturbation technique privacy‐preserving rotation‐based condensation algorithm for privacy preserving in big data stream using Internet of Things
Author(s) -
N Gayathri Devi,
K Manikandan
Publication year - 2020
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3970
Subject(s) - computer science , data stream mining , scalability , data mining , big data , data stream , the internet , cloud computing , k anonymity , information privacy , algorithm , computer security , database , world wide web , telecommunications , operating system
Several concerns are raised due to the widespread technology of Internet of Things and big data, which possess private and protection of information. Several researchers have analyzed different privacy preserving techniques, which still cannot provide equal stability between the data privacy and the utility and improvement in the scalability and efficiency. Data mining is one of the prominent technologies, which extracts reliable and useful knowledge from vast amount of information. Henceforth, mining of data stream have become a most popular and important research issue. Due to fast growth in the data generation, the mechanism of privacy preserving with high utility and security becomes more necessary. In this research, an improved efficient perturbation method for data stream named privacy‐preserving rotation‐based condensation algorithm with geometric transformation is proposed that delivers high data utility when compared with other existing techniques. This improved method gives high resilience against the attacks during the process of data reconstruction. Simulation result shows that the proposed method can acquire data privacy and improves accuracy during mining of data streams in which the analysis is performed for different datasets in which the proposed technique obtains more than 95% when compared with original dataset.