PSSPR: A Source Location Privacy Protection Scheme Based on Sector Phantom Routing in WSNs

Source location privacy (SLP) protection is an emerging research topic in wireless sensor networks. Because the source location represents the valuable information of the target being monitored and tracked, it is of great practical significance to achieve a high degree of privacy of the source location. Although many studies based on phantom nodes have alleviates the protection of SLP to some extent. It is urgent to solve the problems, such as complicate the ac path between nodes, improve the centralized distribution of phantom nodes near the source nodes and reduce the network communication overhead. In this paper, protection scheme based on sector phantom routing (PSSPR) routing is proposed as a visible approach to address SLP issues. We use the coordinates of the center node V to divide sector domain, which act an important role in generating a new phantom node. The phantom nodes perform specified routing policies to ensure that they can choose various locations. In addition, the directed random route can ensure that data packets avoid the visible range when they move to the sink node hop by hop. Thus, the source location is protected. Theoretical analysis and simulation experiments show that this protocol achieves higher security of source node location with less communication overhead.

[1]  Youliang Tian,et al.  Rational Protocols and Attacks in Blockchain System , 2020, Secur. Commun. Networks.

[2]  Liang Zhang,et al.  Organizational memory: reducing source-sink distance , 1997, Proceedings of the Thirtieth Hawaii International Conference on System Sciences.

[3]  Lei Kang,et al.  Protecting Location Privacy in Large-Scale Wireless Sensor Networks , 2009, 2009 IEEE International Conference on Communications.

[4]  Yonggang Wen,et al.  Credit routing for source-location privacy protection in wireless sensor networks , 2012, 2012 IEEE 9th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2012).

[5]  Jiguo Yu,et al.  Wireless Communications and Mobile Computing Blockchain-Based Trust Management in Distributed Internet of Things , 2020, Wirel. Commun. Mob. Comput..

[6]  Sang Hyuk Son,et al.  Wireless Sensor Networks for In-Home Healthcare: Potential and Challenges , 2005 .

[7]  Ramalatha Marimuthu,et al.  A Survey about WSN and IoT Based Health Care Applications and ADPLL Contribution for Health Care Systems , 2019, 2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST).

[8]  Samy El-Tawab,et al.  Improving the security of wireless sensor networks in an IoT environmental monitoring system , 2016, 2016 IEEE Systems and Information Engineering Design Symposium (SIEDS).

[9]  Ho-fung Leung,et al.  Incentive compatible and anti-compounding of wealth in proof-of-stake , 2020, Inf. Sci..

[10]  Xiaomei Yu,et al.  A systematic mapping study for blockchain based on complex network , 2020, Concurr. Comput. Pract. Exp..

[11]  Petros Spachos,et al.  Angle-Based Dynamic Routing Scheme for Source Location Privacy in Wireless Sensor Networks , 2014, 2014 IEEE 79th Vehicular Technology Conference (VTC Spring).

[12]  Janusz Furtak,et al.  Security techniques for the WSN link layer within military IoT , 2016, 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT).

[13]  Peng Hu Location Privacy Preservation in Wireless Sensor Networks , 2015 .

[14]  Wade Trappe,et al.  Source-location privacy in energy-constrained sensor network routing , 2004, SASN '04.

[15]  Xiaomei Yu,et al.  Research cooperations of blockchain: toward the view of complexity network , 2020, Journal of Ambient Intelligence and Humanized Computing.

[16]  Yuling Chen,et al.  Semi‐selfish mining based on hidden Markov decision process , 2021, Int. J. Intell. Syst..

[17]  Miquel Oliver,et al.  CUIDATS: An RFID-WSN hybrid monitoring system for smart health care environments , 2018, Future Gener. Comput. Syst..

[18]  Wang Wei-ping,et al.  A Source-Location Privacy Protocol in WSN Based on Locational Angle , 2008, 2008 IEEE International Conference on Communications.

[19]  Jianxiong Zhou,et al.  A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks , 2015, Sensors.

[20]  Ravi Sankar,et al.  A Survey of Intrusion Detection Systems in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[21]  Mihai T. Lazarescu,et al.  Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications , 2013, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[22]  Fengyin Li,et al.  Belief and fairness: A secure two-party protocol toward the view of entropy for IoT devices , 2020, J. Netw. Comput. Appl..