Computer Science ›› 2017, Vol. 44 ›› Issue (2): 93-97.doi: 10.11896/j.issn.1002-137X.2017.02.012

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D-VSSP:Distributed Social Network Privacy Preserving Algorithm

ZHANG Xiao-lin, ZHANG Chen, ZHANG Wen-chao, ZHANG Huan-xiang and YU Fang-ming   

  • Online:2018-11-13 Published:2018-11-13

Abstract: The processing efficiency of traditional social network privacy preserving technology for large-scale social network data is low.To solve this problem,a distributed vertex splitting social network privacy preserving(D-VSSP) algorithm was proposed.D-VSSP algorithm deals the large-scale social network data in parallel with MapReduce computing model and Pregel-like model.Firstly,using MapReduce distributed model processes the vertex labels with method of label trivialization,grouping trivialized label and exact grouping.And then it realizes distributed vertex splitting anonymity based on the message passing mechanisms of Pregel-like through splitting vertex electing.The experimental results show that the D-VSSP algorithm is superior to the traditional algorithm in processing efficiency for large-scale social network data.

Key words: Distributed algorithm,Large-scale social networks,Privacy-preserving,D-VSSP

[1] LIU X Y,WANG B,YANG X C.Survey on privacy preserving techniques for publishing social network data[J].Journal of Software,2014,5(3):576-590.
[2] TAI C H,YU P S,YANG D N,et al.Privacy-preserving social network publication against friendship attacks[C]∥ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.San Diego,CA,USA,August 2011:1262-1270.
[3] CAMPAN A,TRAIAN M.A clustering approach for data and structural anonymity in social networks[J].In Privacy,Security,and Trust in KDD Workshop,2008,2(8):33-54.
[4] CORMODE G,SRIVASTAVA D,YU T,et al.Anonymizing bipartite graph data using safe groupings[J].Vldb Journal,2008,1(1):833-844.
[5] HAY M,MIKLAU G,JENSEN D,et al.Resisting structuralre-identification in anonymized social networks[J].Proceedings of the Vldb Endowment,2008,1(1):797-823.
[6] WANG Y,XIE L,ZHENG B,et al.Utility-Oriented K-Anonymization on Social Networks[C]∥Database Systems for Advanced Applications-16th International Conference(DASFAA 2011).Hong Kong,China,2011:78-92.
[7] CHENG J,FU W C,LIU J.K-isomorphism:Privacy preserving network publication against structural attacks[C]∥ACM SIGMOD International Conference on Management of Data(SIGMOD 2010).Indianapolis,Indiana,USA,June 2010:459-470.
[8] WU W,XIAO Y,WANG W,et al.k-symmetry model for identity anonymization in social networks[C]∥International Confe-rence on Extending Database Technology.ACM,2010:111-122.
[9] ZOU L,CHEN L,ZSU M T.k-automorphism:a general frame-work for privacy preserving network publication[J].Proceedings of the Vldb Endowment,2009,2(1):946-957.
[10] LIU X,YANG X.A Generalization Based Approach for Anonymizing Weighted Social Network Graphs[M]∥Web-Age Information Management.Springer Berlin Heidelberg,2011:118-130.
[11] DAS S,EGECIOGLU O,EL ABBADI A.Anonymizing weigh-ted social network graphs[C]∥International Conference on Data Engineering.IEEE,2010:904-907.
[12] LIU X Y,YANG X C.Protecting sensitive relationships against inference attacks in social networks[C]∥International Conference on Database Systems for Advanced Applications.Springer-Verlag,2012:335-350.
[13] SUN Y,YUAN Y,WANG G,et al.Splitting anonymization:a novel privacy-preserving approach of social network[J].Know-ledge and Information Systems,2015,1(2):1-29.
[14] ZAKERZADEH H,AGGARWAL C C,Barker K.Big GraphPrivacy[C]∥EDBT/ICDT Workshops.2015:255-262.
[15] QIN L,YU J X,CHANG L,et al.Scalable big graph processing in MapReduce[C]∥SIGMOD.2014:827-838.
[16] SALIHOGLU S,WIDOM J.Optimizing graph algorithms onpregel-like systems[J].Proceedings of the Vldb Endowment,2014,7(7):577-588.

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