Source-Location Privacy Full Protection Based On Secret Sharing Technique In Wireless Sensor Networks

In many scenarios,the locations of the monitored targets need to be reported by the source nodes and they should remain anonymous in wireless sensor networks(WSNs)to guarantee the security of the network and monitored targets.Consequently,source-location privacy protection is an important research topic in WSNs and many schemes have been designed based on different adversarial models.In this paper,a scheme named Source-location Privacy Full Protection(SPFP)is proposed.For the first time,we consider a more practical adversarial model called smart adversarial model which is a combination of the global and local models.In the initial,we assume that the adversary stays around the sink node and try to trace back to the source node by the local adversary model.However,once the adversary finds a suspicious region that likely covers the source node,he deploys all the resources in this region and collects all the radio information of the sensor nodes.Then,he becomes a global adversary.Apparently,the smart adversarial model is more reasonable compared with the traditional models and it can help us to design a more practical source-location privacy protection scheme.To defend against the novel adversary,we first design a light-weight(t,n)-threshold message sharing scheme based on congruence equations and the shares are short in length which can be processed and transmitted in an energy-efficient manner.Considering that the proposed secret sharing scheme mainly employs the add operations and module operations,it is of very low computation complexity.Therefore,it is energy efficient.The correctness and security of the scheme are proved in theorems.In addition,the proposed message sharing scheme can highly tolerate the unreliability of sensor nodes and provides more reliable data transmission mechanism for the networks.In the process of delivering a message to the sink node,the source node first constructs a cloud around itself based on the shares and dummy packages to hide its exact location.In this paper,we propose an algorithm that can generate the cloud with irregular shapes.As a consequence,the relationship between the shape of the clouds and the exact location of the source node is destroyed,and hence it is extremely difficult for the adversary to locate the source node based on the shape of the cloud.The radio actions of the nodes in the cloud are carefully arranged to conceal the real shares among the fake shares and make the nodes statistically indistinguishable.When the real shares are delivered to the border of the cloud,a set of fake source nodes are randomly selected.The fake source nodes are responsible of transmitting the real shares to the sink node.To safely deliver the real shares between the fake source node and the sink node,we design a novel random routing algorithm named All-direction Random Routing(ARR).In the initial,the fake source node needs to select a virtual location that defines an agent node indirectly.Then a sophisticated mechanism is designed to guarantee that the real share can be always successfully delivered to the agent node.Then,the agent node delivers the real share to the sink node where the original message can be reconstructed.The ARR algorithm can be employed alone to protect the source-location privacy or as a module of the all-direction source location protection scheme.Based on the secret sharing scheme,cloud construction algorithm and the random routing algorithm,we can guarantee that the adversary cannot collect any valuable information about the source node in the whole process of delivering a message from the source node to the sink node.Therefore,we call the proposed scheme as the Source-location Privacy Full Protection(SPFP)scheme.We conduct a set of simulations based on the ns-3 simulator and compare the SPFP scheme with several existing source-location privacy protection schemes.Simulation results illustrate that our scheme can provide very strong protection on the source-location privacy with a slight increasing of energy consumption.