IoT-Based source location privacy preservation: The case of habitat monitoring

Abstract

The Internet of Things (IoT) comprises the most essential elements including sensors/devices, connectivity, processing of information, and interfaces for users. The sensor nodes are responsible for detecting a variety of things including temperature, humidity, smoke, etc. A network madeupofwirelesslyconnecteddeployedsensornodesisknownasawirelesssensornetwork (WSN). Sensor nodes (also known as motes) contain a transmitter and a receiver, a central processor for performing mathematical calculations, and a memory for storing data. Wireless Sensor Networks (WSNs) and their derivatives such as the Internet of Things (IoT) and the Internet of Industrial Things (IIoT) are used in different domains such as agriculture, health care, smart cities, vehicular technology, etc. The Use of WSN and IoT has not been restricted to those classic applications but has also spread its applicability to even monitor valuable objects, like reporting real-time military information in the battlefield and endangered species location in habitat monitoring. The nature of wireless communication links makes its privacy the utmost important consideration due to its openness and lack of protected physical boundaries compared to wired networks, which may lead to unauthorized interruption and detection. Security and privacy, particularly the anonymity of the source locations, have proven to be significant obstacles to the successful implementation of WSNs. A further issue is that sensor nodes are battery-powered which makes it difficult to create network protocols that could enhance WSN privacy and security because most of those protocols are energy-intensive and replacing dead nodes is very challenging. Therefore, those energy-intensive privacy protocols are not recommended for sensor networks with limited resources. This thesis aims at proposing contextual source location privacy preservation protocols which achieve enhanced privacy, network lifetime, and achieving privacy, lifetime without influencing latency. It further deals with analyzing the effect of sensor nodes’ radio range on privacy strength and network longevity. In this thesis, we consider the case of habitat monitoring, where sensor nodes are deployed strategically in natural habitat to provide real-time updates on the locations of endangered species to a central base station. To handle the above mentioned issues, we first propose a biased random walk and greedy walk-based routing protocol which uses a three- or four-phase routing strategy. The objective of the solution is to achieve a uniform amount of privacy irrespectiveofthepositionoftheassetinthenetworkwithoutcompromisingthenetworklifetime. The proposed protocol outperforms the existing random walk-based source location privacy schemes in terms of safety period without affecting lifetime and it achieves a uniform privacy levelinallnetworksettings. Secondly,weproposeatotalrandomizedapproachthatemploysa reverse random walk followed by a walk on annular rings, to create divergent routing paths in the network, and finally, the walk on dynamic rings together with min-hop walk to deliver the xi packetstowardthebasestation. Inthissolution,uniformprivacyisachievedwithenhancement in the network lifetime, unlike in the first solution where privacy is enhanced without an increaseinthenetworklifetime. Comparingthesecondsolutiontothefirstone,theprivacylevel isimprovedsincethepackettraveliscompletelyrandomized. However,theincreaseinprivacy in all solutions comes at the cost of high latency. To overcome this limitation, we proposed animprovedrandomwalk-basedsolutionthatenhancesbothprivacylevelandlifetimewithout affecting latency. Finally, we study the impact of the sensor nodes’ radio range on privacy strength and the Network lifetime metrics in Source location privacy schemes of WSNs. Weassesstheeffectivenessofthesuggestedschemesandcontrastthemwiththecommonly employedcurrentprivacypreservationtechniques. Bothanalyticalandsimulationresultsshow that our proposed approaches produced good performance benefits in terms of privacy, uncertainty, path randomness, and network longevity.