Telecommunications Science ›› 2016, Vol. 32 ›› Issue (7): 90-96.doi: 10.11959/j.issn.1000-0801.2016135

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Hybrid k-anonymity approach based on TDS and BUG under the environment of big data cloud

Xiaofeng FAN1,Feng YAN2,Yang LIU3   

  1. 1 Inner Mongolia Business & Trade Vocational College,Hohhot 010070,China
    2 Vocational and Technical College of Inner Mongolia Agricultural University,Baotou 014109,China
    3 Hohhot Vocational College,Hohhot 010050,China
  • Online:2016-07-20 Published:2017-04-26

Abstract:

As the issue of low efficiency and poor scalability in general sub-tree anonymous method of treating big data,a bottom-up generalization(BUG) method with scalability was proposed,and on this basis,combined with the existing top-down specialization(TDS),a hybrid approach was formed.In the proposed method,k-anonymity was being as a privacy model,the compositions of TDS and BUG were developed with mapping simplification,and higher scalability through powerful cloud computing capabilities were achieved.The proposed mapping simplification BUG could insert a new candidate after several cycles of generalization,and would not affect information loss of another generalization.Given the complexity of the relationship between workload balancing point K and anonymous parameter k,mapping simplifications of BUG and TDS were combined to form a hybrid approach.Experimental results demonstrate the effectiveness of the proposed method and compared with TDS and BUG,the efficiency and scalability of hybrid method are greatly improved.

Key words: cloud computing, sub-tree anonymous, big data, generalization, specialization, mapping simplification

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