Research on Privacy Preservation of Big Data Challenges and Real Time Applications
Sukhjeet Kaur1, BK Verma2 

1Sukhjeet Kaur, Centre for Science and Environment, Council for Exceptional Children  Landran, Kurali, India.
2Prof (Dr.) B.K VERMA, Centre for Science and Environment, Council for Exceptional Children Landran, Rajasthan, India.

Manuscript received on 04 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 3813-3817 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2388078219/19©BEIESP | DOI: 10.35940/ijrte.B2388.078219
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Abstract: Our examination work is the most slanting since it relates to the security issues which increase, well ordered in view of the casual association inclines in society. In this paper we address the issue of uncovering an individual’s information; the philosophy depends for the most part on the K-anonymity with the possibility of unimportant theory, which gets the property of the release strategy not to ravage the data more than anticipated to achieve K-lack of definition. We talk about the colossal data in detail how it is useful to guarantee an immense volume of information without change the arrangement of one of a kind data. Data stored in different forms is anonymise efficiently without affecting the integrity if data by using K-Anonymity and Artificial Bee Colony algorithm respectively. We similarly give base on security and insurance strategies and to avoid the interference. We use the phony bumble bee settlement (ABC) count to propel the tremendous enlightening accumulation. We exhibit the result in graphically the sum we improve the insurance from the as of proposed system. Here both K-Anonymity and ABC Algorithm is used (mixed) which never took care by executing parallel.
Index Terms: Big Data, Social Media, Privacy Preservation, K-Anonymity, Average Path Length, Artificial Bee Colony, Normal Change of Sensitive Label Path, Remaining Ratio of Top Influential Users.

Scope of the Article: Big Data