Zhang, X., Yang, C., Nepal, S., Liu, C., Dou, W. and Chen, J. (2013) A Map Reduce Based Approach of Scalable Multidimensional Anonymization for Big Data Privacy Preservation on Cloud. International Conference on Cloud and Green Computing, 105-112.
https://doi.org/10.1109/CGC.2013.24

has been cited by the following article:

• TITLE: Towards the Development of Best Data Security for Big Data

  AUTHORS: Yuan Tian

  KEYWORDS: Big Data Analytics, Secure Big Data, Security Intelligence Model

  JOURNAL NAME: Communications and Network, Vol.9 No.4, November 30, 2017

  ABSTRACT: Big data is becoming a well-known buzzword and in active use in many areas. Because of the velocity, variety, and volume of big data, security and privacy issues are magnified, which results in the traditional protection mechanisms for structured small scale data are inadequate for big data. Sensitivities around big data security and privacy are a hurdle that organizations need to overcome. In this paper, we review the current data security in big data and analysis its feasibilities and obstacles. Besides, we also introduced intelligent analytics to enhance security with the proposed security intelligence model. This research aims to summarize, organize and classify the information available in the literature to identify any gaps in current research and suggest areas for scholars and security researchers for further investigation.