Source location privacy-aware data aggregation scheduling for wireless sensor networks

Source Location Privacy (SLP) is an important property for the class of asset monitoring problems in wireless sensor networks (WSNs). SLP aims to prevent an attacker from finding a valuable asset when a WSN node is broadcasting information due to the detection of the asset. Many different methods of protecting the location of a source have been devised for a variety of attacker models. Most common methods of providing SLP operate at the routing level of the network stack, imposing a high message overhead on the SLP-aware routing protocol. The objective of this thesis is to investigate the novel problem of utilising TDMA slot assignment schedules at the MAC layer in order to provide SLP. These schedules each give rise to different traffic patterns, manipulation of which can be used to divert an attacker away from the asset. Four main contributions are presented. First, a novel formalisation of a parameterised eavesdropping attacker model is created, allowing for comparison of attackers of different strengths. Second, a genetic algorithm is used to generate TDMA Data Aggregation Scheduling (DAS) schedules that contain a diversionary route that leads the attacker away from the source. Third, a distributed algorithm is created to perform the same task while operating online on a WSN. Finally, another distributed algorithm is presented that provides fault-tolerant guarantees with a minimal drop in performance

Source Location Privacy-Aware Data Aggregation Scheduling for Wireless Sensor Networks

Source location privacy (SLP) is an important property for the class of asset monitoring problems in wireless sensor networks (WSNs). SLP aims to prevent an attacker from finding a valuable asset when a WSN node is broadcasting information due to the detection of the asset. Most SLP techniques focus at the routing level, with typically high message overhead. The objective of this paper is to investigate the novel problem of developing a TDMA MAC schedule that can provide SLP. We make a number of important contributions: (i) we develop a novel formalisation of a class of eavesdropping attackers and provide novel formalisations of SLP-aware data aggregation schedules (DAS), (ii) we present a decision procedure to verify whether a DAS schedule is SLP-aware, that returns a counterexample if the schedule is not, similar to model checking, and (iii) we develop a 3-stage distributed algorithm that transforms an initial DAS algorithm into a corresponding SLP-aware schedule against a specific class of eavesdroppers. Our simulation results show that the resulting SLP-aware DAS protocol reduces the capture ratio by 50% at the expense of negligable message overhead

Source location privacy in wireless sensor networks under practical scenarios : routing protocols, parameterisations and trade-offs

As wireless sensor networks (WSNs) have been applied across a spectrum of application domains, source location privacy (SLP) has emerged as a significant issue, particularly in security-critical situations. In seminal work on SLP, several protocols were proposed as viable approaches to address the issue of SLP. However, most state-of-the-art approaches work under specific network assumptions. For example, phantom routing, one of the most popular routing protocols for SLP, assumes a single source. On the other hand, in practical scenarios for SLP, this assumption is not realistic, as there will be multiple data sources. Other issues of practical interest include network configurations. Thus, thesis addresses the impact of these practical considerations on SLP. The first step is the evaluation of phantom routing under various configurations, e.g., multiple sources and network configurations. The results show that phantom routing does not scale to handle multiple sources while providing high SLP at the expense of low messages yield. Thus, an important issue arises as a result of this observation that the need for a routing protocol that can handle multiple sources. As such, a novel parametric routing protocol is proposed, called phantom walkabouts, for SLP for multi-source WSNs. A large-scale experiments are conducted to evaluate the efficiency of phantom walkabouts. The main observation is that phantom walkabouts can provide high level of SLP at the expense of energy and/or data yield. To deal with these trade-offs, a framework that allows reasoning about trade-offs needs to develop. Thus, a decision theoretic methodology is proposed that allows reasoning about these trade-offs. The results showcase the viability of this methodology via several case studies

Near optimal routing protocols for source location privacy in wireless sensor networks: modelling, design and evaluation

Wireless Sensor Networks (WSNs) are collections of small computing devices that are used to monitor valuable assets such as endangered animals. As WSNs communicate wirelessly they leak information to malicious eavesdroppers. When monitoring assets it is important to provide Source Location Privacy (SLP), where the location of the message source must be kept hidden. Many SLP protocols have been developed by designing a protocol using intuition before evaluating its performance. However, this does not provide insight into how to develop optimal approaches. This thesis will present an alternate approach where the SLP problem is modelled using different techniques to give an optimal output. However, as this optimal output is typically for a restricted scenario, algorithms that trade optimality for generality are subsequently designed. Four main contributions are presented. First, an analysis is performed based on entropy and divergence to gain insight into how to reduce the information an attacker gains via the use of competing paths, and ways to compare the information loss of arbitrary routing protocols. Secondly, the SLP problem is modelled using Integer Linear Programming. The model result guides the design of a generic protocol called ILPRouting that groups messages together to reduce the moves an attacker makes. Thirdly, a timing analysis of when events occur is used to dynamically determine fake source parameters for the Dynamic and DynamicSPR algorithms. These fake sources lure the attacker to their location instead of the real source. Finally, the first SLP-aware duty cycle is investigated, and implemented for DynamicSPR to make it more energy efficient. These techniques are evaluated through simulations and deployments on WSN testbeds to demonstrate their effectiveness