Abstract
The Big Data plays a valuable role in large scale information management that overshoots the potential of traditional data processing technologies. The importance of volume, velocity, variety, veracity and value of big data made researchers to put efforts to handle them efficiently. On considering the 5V’s of big data, if the veracity characteristic is not well focused, then the idea of big data will not be widely recognized. Advances in technology allow users to extract and utilize the big data which make data privacy violations in maximum cases. Also the data used for big data analytics may include restricted information. So it is necessary to protect and notice whether this kind of data is used with certain principles. In this paper we formalize a Bi-level security mechanism called Cosine Similarity with P-Stability for data privacy and graph protection in one of the big data environment called Online Social Network.
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The first author would like to thank the management of Kalasalingam University for providing financial assistance under the University Research Fellowship.
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Franklin Vinod, D., Vasudevan, V. (2017). A Bi-level Security Mechanism for Efficient Protection on Graphs in Online Social Network. In: Arumugam, S., Bagga, J., Beineke, L., Panda, B. (eds) Theoretical Computer Science and Discrete Mathematics. ICTCSDM 2016. Lecture Notes in Computer Science(), vol 10398. Springer, Cham. https://doi.org/10.1007/978-3-319-64419-6_9
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DOI: https://doi.org/10.1007/978-3-319-64419-6_9
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