Query Privacy Preserving for Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are increasingly involved in many applications. However, communication overhead and energy efficiency of sensor nodes are the major concerns in WSNs. In addition, the broadcast communication mode of WSNs makes the network vulnerable to privacy disclosure when the sensor nodes are subject to malicious behaviours. Based on the abovementioned issues, we present a Queries Privacy Preserving mechanism for Data Aggregation (QPPDA) which may reduce energy consumption by allowing multiple queries to be aggregated into a single packet and preserve data privacy effectively by employing a privacy homomorphic encryption scheme. The performance evaluations obtained from the theoretical analysis and the experimental simulation show that our mechanism can reduce the communication overhead of the network and protect the private data from being compromised.

[1]  Xue Liu,et al.  PDA: Privacy-Preserving Data Aggregation in Wireless Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[2]  Aggelos Kiayias,et al.  Exact In-Network Aggregation with Integrity and Confidentiality , 2012, IEEE Transactions on Knowledge and Data Engineering.

[3]  Huaqun Wang,et al.  Incentive and Unconditionally Anonymous Identity-Based Public Provable Data Possession , 2019, IEEE Transactions on Services Computing.

[4]  Yang Xiao,et al.  Integrity protecting hierarchical concealed data aggregation for wireless sensor networks , 2011, Comput. Networks.

[5]  Lina Ni,et al.  DP-MCDBSCAN: Differential Privacy Preserving Multi-Core DBSCAN Clustering for Network User Data , 2018, IEEE Access.

[6]  Jiguo Yu,et al.  Edge Computing Security: State of the Art and Challenges , 2019, Proceedings of the IEEE.

[7]  C. Castelluccia,et al.  Efficient aggregation of encrypted data in wireless sensor networks , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[8]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[9]  Rui Zhang,et al.  Secure Range Queries in Tiered Sensor Networks , 2009, IEEE INFOCOM 2009.

[10]  K. R. Venugopal,et al.  SDAMQ: Secure Data Aggregation for Multiple Queries in Wireless Sensor Networks☆ , 2016 .

[11]  Yang Xiao,et al.  Secure data aggregation in wireless sensor networks: A comprehensive overview , 2009, Comput. Networks.

[12]  Alex X. Liu,et al.  SafeQ: Secure and Efficient Query Processing in Sensor Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[13]  Jiguo Yu,et al.  Achieving Personalized $k$-Anonymity-Based Content Privacy for Autonomous Vehicles in CPS , 2020, IEEE Transactions on Industrial Informatics.

[14]  Geng Yang,et al.  Precision-Enhanced and Encryption-Mixed Privacy-Preserving Data Aggregation in Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[15]  Keqiu Li,et al.  Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks , 2011, Comput. Commun..

[16]  Jiguo Yu,et al.  A Privacy Preserving Communication Protocol for IoT Applications in Smart Homes , 2016, 2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI).

[17]  Shanshan Li,et al.  A Secure Data Aggregation Approach Based on Monitoring in Wireless Sensor Networks , 2011, 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks.

[18]  Xi Chen,et al.  Mutual privacy-preserving regression modeling in participatory sensing , 2013, 2013 Proceedings IEEE INFOCOM.

[19]  Dr.S. Govindarajan,et al.  Data Aggregation in Wireless Sensor Networks , 2011 .

[20]  KwangJin Park,et al.  A Privacy-Preserving Spatial Index for Spatial Query Processing , 2018, Wirel. Commun. Mob. Comput..

[21]  Md.Asdaque Hussain,et al.  WSN research activities for military application , 2009, 2009 11th International Conference on Advanced Communication Technology.

[22]  Jiguo Yu,et al.  A Differential-Private Framework for Urban Traffic Flows Estimation via Taxi Companies , 2019, IEEE Transactions on Industrial Informatics.

[23]  Xin-Ping Guan,et al.  Topology control based on optimally rigid graph in wireless sensor networks , 2013, Comput. Networks.

[24]  Bo Sheng,et al.  Verifiable Privacy-Preserving Range Query in Two-Tiered Sensor Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[25]  Josep Domingo-Ferrer,et al.  Anonymous and secure aggregation scheme in fog-based public cloud computing , 2018, Future Gener. Comput. Syst..

[26]  Tao Xiang,et al.  Two Secure Privacy-Preserving Data Aggregation Schemes for IoT , 2019, Wirel. Commun. Mob. Comput..

[27]  Qiang Zhou,et al.  An Efficient Secure Data Aggregation Based on Homomorphic Primitives in Wireless Sensor Networks , 2014, Int. J. Distributed Sens. Networks.

[28]  Sherali Zeadally,et al.  Lightweight Data Aggregation Scheme against Internal Attackers in Smart Grid Using Elliptic Curve Cryptography , 2017, Wirel. Commun. Mob. Comput..

[29]  Jiguo Yu,et al.  Latent-Data Privacy Preserving With Customized Data Utility for Social Network Data , 2018, IEEE Transactions on Vehicular Technology.

[30]  Shaojie Tang,et al.  Privacy-preserving data aggregation without secure channel: Multivariate polynomial evaluation , 2013, 2013 Proceedings IEEE INFOCOM.

[31]  Chinta Someswara Rao,et al.  Energy-Efficient Data Route-in-Network Aggregation with Secure EEDRINA , 2018 .

[32]  Dirk Westhoff,et al.  CDA: concealed data aggregation for reverse multicast traffic in wireless sensor networks , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[33]  Huaqun Wang,et al.  Blockchain-Based Private Provable Data Possession , 2019, IEEE Transactions on Dependable and Secure Computing.

[34]  Liehuang Zhu,et al.  An Efficient Data Aggregation Protocol Concentrated on Data Integrity in Wireless Sensor Networks , 2013, Int. J. Distributed Sens. Networks.

[35]  K. Nahrstedt,et al.  iPDA: An integrity-protecting private data aggregation scheme for wireless sensor networks , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[36]  Yanfei Lu,et al.  Re-ADP: Real-Time Data Aggregation with Adaptive ω-Event Differential Privacy for Fog Computing , 2018, Wirel. Commun. Mob. Comput..

[37]  Anmin Fu,et al.  Provable Data Possession with Outsourced Data Transfer , 2019, IEEE Transactions on Services Computing.

[38]  Huang Min,et al.  Building a Smart Home System with WSN and Service Robot , 2013, 2013 Fifth International Conference on Measuring Technology and Mechatronics Automation.

[39]  Ketan D. Bodhe,et al.  Secure data aggregation in WSN using iterative filtering algorithm , 2017, 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA).

[40]  Yan Sun,et al.  Z-O Encoding Based Privacy-preserving MAX/MIN Query Protocol in Two-tiered Wireless Sensor Networks: Z-O Encoding Based Privacy-preserving MAX/MIN Query Protocol in Two-tiered Wireless Sensor Networks , 2014 .

[41]  Keith B. Frikken,et al.  General secure sensor aggregation in the presence of malicious nodes , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[42]  Gene Tsudik,et al.  QUEST Software and , 2022 .