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

Abstract

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.<div>The work also presents future research direction for prospective researcher.</div>

Analysis of Improved Particle Swarm Algorithm in Wireless Sensor Network Localization

“…Raja et al proposed two solutions for multi-asset scenarios in order to be able to protect the source location privacy in WSNs and reduce the impact of random walk related methods. After comparing the performance of the related solutions, it is known that the use of the solution can better protect the location privacy [9]. Varshovi et al address the problem of high volume of multimedia data in Wireless Multimedia Sensor Network (WMSN) by using the related processor for local image processing as a way to perform certain motion detection and send its related information to the base station The results show the effectiveness of the detection method.…”

“…Set the optimal position as The mapping of i g to the domain of the definition of the chaos model [0,1] is done by equation (9).…”