Secure Spatial Network Queries on Cloud Platform

With massive real-world networks added with spatial attributes, query processing in spatial networks has been widely used in real-life applications. Considering the high costs of spatial network queries, outsourcing querying services to cloud provides a cost-effective way for data owners. However, directly outsourcing such services may cause serious privacy concerns. To address this privacy problem, existing studies apply anonymous or differential privacy techniques on spatial network queries, which are not under the semi-trusted secure model. Other existing works primarily focus on query processing over either encrypted spatial or network data, which cannot directly be applied to work out the secure spatial network query problem. To this end, we define and study Secure Spatial Network kNN Query (SSNQ) problem on cloud platform. We first present Basic Secure Spatial Network kNN Query (BSSNQ) method, in which we compute secure kNN for the query node to construct candidate sequences using secure subprotocols. With pre-encrypted network distances, we then compute shortest paths between the query node and each candidate, and securely update the candidate sequences according to Euclidean restriction to derive final query results. To improve the efficiency of BSSNQ, we further propose Heuristic Secure Spatial Network kNN Query (HSSNQ) method, which securely calculates shortest paths from the query node to the visiting nodes iteratively, and use optimistic estimate distances as the key to lead the heuristic search within a priority queue. Thorough analysis shows the security and complexity of the proposed methods, and extensive experimental results on real datasets demonstrate the efficiency of the query performance.

[1]  Roger Zimmermann,et al.  Privacy Protected Spatial Query Processing for Advanced Location Based Services , 2009, Wirel. Pers. Commun..

[2]  Xintao Wu,et al.  Preserving Differential Privacy in Degree-Correlation based Graph Generation , 2013, Trans. Data Priv..

[3]  Jae-Woo Chang,et al.  A kNN query processing algorithm using a tree index structure on the encrypted database , 2016, 2016 International Conference on Big Data and Smart Computing (BigComp).

[4]  Peng Jiang,et al.  Privacy-enhanced attribute-based private information retrieval , 2018, Inf. Sci..

[5]  Chris Clifton,et al.  A secure distributed framework for achieving k-anonymity , 2006, The VLDB Journal.

[6]  Xiaohui Yu,et al.  Privacy-Preserving Reachability Query Services for Massive Networks , 2016, CIKM.

[7]  Cong Wang,et al.  Privacy-Preserving Query over Encrypted Graph-Structured Data in Cloud Computing , 2011, 2011 31st International Conference on Distributed Computing Systems.

[8]  Cyrus Shahabi,et al.  Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases , 2004, VLDB.

[9]  Rafail Ostrovsky,et al.  Distributed Oblivious RAM for Secure Two-Party Computation , 2013, TCC.

[10]  Jianliang Xu,et al.  A Cloaking Algorithm Based on Spatial Networks for Location Privacy , 2008, 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008).

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

[12]  Amos Fiat,et al.  Zero-knowledge proofs of identity , 1987, Journal of Cryptology.

[13]  Zongda Wu,et al.  Secure Shortest Path Search over Encrypted Graph Supporting Synonym Query in Cloud Computing , 2016, 2016 IEEE Trustcom/BigDataSE/ISPA.

[14]  Shazia Wasim Sadiq,et al.  Instance optimal query processing in spatial networks , 2009, The VLDB Journal.

[15]  Xiang Cheng,et al.  Privacy-Preserving Top-k Nearest Keyword Search on Outsourced Graphs , 2016, 2016 IEEE Trustcom/BigDataSE/ISPA.

[16]  Oded Goldreich,et al.  The Foundations of Cryptography - Volume 2: Basic Applications , 2001 .

[17]  Oded Goldreich,et al.  Foundations of Cryptography: Volume 2, Basic Applications , 2004 .

[18]  Wei Jiang,et al.  An efficient and probabilistic secure bit-decomposition , 2013, ASIA CCS '13.

[19]  Pascal Paillier,et al.  Public-Key Cryptosystems Based on Composite Degree Residuosity Classes , 1999, EUROCRYPT.

[20]  Jian Pei,et al.  Secure Skyline Queries on Cloud Platform , 2017, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).

[21]  Jae-Woo Chang,et al.  A Privacy Protected k-NN Query Processing Algorithm Based on Network Voronoi Diagram in Spatial Networks , 2014, IEICE Trans. Inf. Syst..

[22]  George Kollios,et al.  GRECS: Graph Encryption for Approximate Shortest Distance Queries , 2015, IACR Cryptol. ePrint Arch..

[23]  Yufei Tao,et al.  Query Processing in Spatial Network Databases , 2003, VLDB.

[24]  Wei Jiang,et al.  Secure k-nearest neighbor query over encrypted data in outsourced environments , 2013, 2014 IEEE 30th International Conference on Data Engineering.

[25]  Hanan Samet,et al.  Memory-efficient algorithms for spatial network queries , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[26]  Hanan Samet,et al.  Scalable network distance browsing in spatial databases , 2008, SIGMOD Conference.