Privacy-Protection Path Finding Supporting the Ranked Order on Encrypted Graph in Big Data Environment

Since data outsourcing in big data environment become popular and become a trend, large quantities of graph data are outsourced to the big data server for saving cost. As the big data server can not be fully reliable, people usually encrypt the graph data before they are outsourced to the big data platform for the privacy protection. The path finding is a frequently-used action and can be useful for production and living. The path finding supporting the ranked order is a more useful operation, and a user can obtain a ranked search result set. Because of the outsourced graph data being encrypted on the big data server, the path finding supporting the ranked order becomes a task with enough challenge. In this paper, we propose a solution to perform privacy-protection path finding supporting the ranked order on encrypted graph in big data environment (PPFR). Our research uses an encryption mechanism and a ranking strategy to achieve path finding supporting the ranked order. We formally analyze the security of our scheme. We demonstrate the efficiency of our proposed scheme on a real graph data set by experiment.

[1]  Jure Leskovec,et al.  Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters , 2008, Internet Math..

[2]  Zhe Fan,et al.  Privacy-preserving reachability query services for sparse graphs , 2014, 2014 IEEE 30th International Conference on Data Engineering Workshops.

[3]  Baotong Li,et al.  Topology optimization techniques for mobile robot path planning , 2019, Appl. Soft Comput..

[4]  Rafail Ostrovsky,et al.  Searchable symmetric encryption: improved definitions and efficient constructions , 2006, CCS '06.

[5]  Tinghua Ai,et al.  Road network generalization considering traffic flow patterns , 2020, Int. J. Geogr. Inf. Sci..

[6]  Pan Li,et al.  Efficient Secure Outsourcing of Large-Scale Convex Separable Programming for Big Data , 2019, IEEE Transactions on Big Data.

[7]  Xingming Sun,et al.  Semantic-Aware Searching Over Encrypted Data for Cloud Computing , 2018, IEEE Transactions on Information Forensics and Security.

[8]  Zongmin Cui,et al.  Blind Reversible Authentication Based on PEE and CS Reconstruction , 2018, IEEE Signal Processing Letters.

[9]  Eu-Jin Goh,et al.  Secure Indexes , 2003, IACR Cryptol. ePrint Arch..

[10]  Silvio Micali,et al.  Probabilistic Encryption , 1984, J. Comput. Syst. Sci..

[11]  Melissa Chase,et al.  Structured Encryption and Controlled Disclosure , 2010, IACR Cryptol. ePrint Arch..

[12]  Yiming Yang,et al.  Introducing the Enron Corpus , 2004, CEAS.

[13]  Weifeng Chen,et al.  Privacy-assured substructure similarity query over encrypted graph-structured data in cloud , 2014, Secur. Commun. Networks.

[14]  Dawn Xiaodong Song,et al.  Practical techniques for searches on encrypted data , 2000, Proceeding 2000 IEEE Symposium on Security and Privacy. S&P 2000.

[15]  Yinghong Ma,et al.  Structure properties of collaboration network with tunable clustering , 2020, Inf. Sci..

[16]  Hiroyuki Sato,et al.  Scalable and secure access control policy update for outsourced big data , 2018, Future Gener. Comput. Syst..

[17]  Chengsheng Yuan,et al.  A Novel Weber Local Binary Descriptor for Fingerprint Liveness Detection , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[18]  Xingming Sun,et al.  Reversible data hiding with contrast enhancement and tamper localization for medical images , 2017, Inf. Sci..

[19]  Guangyi Wang,et al.  A novel parallel image encryption algorithm based on hybrid chaotic maps with OpenCL implementation , 2020, Soft Computing.

[20]  Hugo Krawczyk,et al.  Highly-Scalable Searchable Symmetric Encryption with Support for Boolean Queries , 2013, IACR Cryptol. ePrint Arch..

[21]  Charalampos Papamanthou,et al.  Dynamic searchable symmetric encryption , 2012, IACR Cryptol. ePrint Arch..

[22]  Mihiri Hewa Bosthanthirige,et al.  Outlier detection in network data using the Betweenness Centrality , 2015 .

[23]  S. Rajsbaum.  Foundations of Cryptography , 2014 .

[24]  Michael Mitzenmacher,et al.  Privacy Preserving Keyword Searches on Remote Encrypted Data , 2005, ACNS.

[25]  Artem A. Sedakov,et al.  Coordinated Influence on the Opinions of Social Network Members , 2020, Autom. Remote. Control..

[26]  Ismaeel Al Ridhawi,et al.  Workflow-Net Based Service Composition Using Mobile Edge Nodes , 2017, IEEE Access.

[27]  Yezid Donoso,et al.  A Prediction Algorithm based on Markov Chains for finding the Minimum Cost Path in a Mobile WSNs , 2019, Int. J. Comput. Commun. Control.

[28]  Jianliang Xu,et al.  Asymmetric structure-preserving subgraph queries for large graphs , 2015, 2015 IEEE 31st International Conference on Data Engineering.

[29]  Zongda Wu,et al.  A Location Privacy-Preserving System Based on Query Range Cover-Up or Location-Based Services , 2020, IEEE Transactions on Vehicular Technology.

[30]  Zongda Wu,et al.  A Barrage Sentiment Analysis Scheme Based on Expression and Tone , 2019, IEEE Access.

[31]  Robert H. Deng,et al.  Flexible Wildcard Searchable Encryption System , 2020, IEEE Transactions on Services Computing.

[32]  Hugo Krawczyk,et al.  Dynamic Searchable Encryption in Very-Large Databases: Data Structures and Implementation , 2014, NDSS.

[33]  Jianliang Xu,et al.  Privacy-Preserving Reachability Query Services , 2014, DASFAA.

[34]  Muttukrishnan Rajarajan,et al.  A parallelized disjunctive query based searchable encryption scheme for big data , 2020, Future Gener. Comput. Syst..

[35]  Florian Kerschbaum,et al.  Searchable Encryption with Secure and Efficient Updates , 2014, CCS.

[36]  Shunli Zhang,et al.  A Novel Range Search Scheme Based on Frequent Computing for Edge-Cloud Collaborative Computing in CPSS , 2020, IEEE Access.

[37]  Joonsang Baek,et al.  Public Key Encryption with Keyword Search Revisited , 2008, ICCSA.

[38]  Dongqi Wang,et al.  A Community Finding Method for Weighted Dynamic Online Social Network Based on User Behavior , 2015, Int. J. Distributed Sens. Networks.