Protecting Source Location Privacy in IoT Enabled Wireless Sensor Networks: the Case of Multiple Assets

Till date source location privacy preserving techniques have aimed at fake backed or fake source approaches. Also, the work is concentrated to a single source scenarios. In this work, aim to explore the random-walk approach to mitigate passive eavesdropping attacker who backtracks to the source of information. Random-walk based solutions have proven to be effective for energy constrained WSNs. However, there is very little work that has worked for the case of multiple asset (sources) scenario till date. To understand the effect of the random-walk based solutions on level of location privacy in WSN intended IoT systems, for the multiple asset scenario, we developed two solutions. Through simulations we show the performance of the proposed two solutions by comparing them with existing random-walk based solutions. Our findings suggest that mere presence of multiple sources in the network alone does not provide location privacy, as one is intended to expect. It rather, need careful planning and designing of routing protocols to provide better privacy in presence of multiple-assets.