Deconstructing source location privacy-aware routing protocols

Concurrency and Computation

2019

Self Cite

Source location privacy (SLP) is an important property for a large class of security-critical wireless sensor network (WSN) applications such as monitoring and tracking. In the seminal work on SLP, phantom routing was proposed as a viable approach to address SLP. However, recent work has shown some limitations of phantom routing such as poor data yield and low SLP. In this paper, we propose phantom walkabouts, a novel and more general version of phantom routing, which performs phantom routes of variable lengths. Through extensive simulations, we show that phantom walkabouts provides high SLP level than phantom routing under specific network configuration. KEYWORDSbiased random walk, phantom routing, phantom walkabouts, source location privacy, wireless sensor networks INTRODUCTIONA wireless sensor network (WSN) consists of a number of tiny devices, known as sensor nodes, that can sense different attributes of the environment and use radio signals to communicate among themselves. WSNs have enabled the development of many novel applications, including asset monitoring, 1 target tracking, 2 and environment control 3 among others, with low levels of intrusiveness. They are also expected to be deployed in safety and security-critical systems, including military 4 and medical services. 5 The communication protocols used in the WSNs must therefore meet a set of stringent security and privacy requirements, dependent on the application.Threats to privacy in monitoring applications can be considered along two dimensions, ie, (1) content-based threats and (2) context-based threats. Content-based privacy threats relate to use of the content of the messages broadcast by sensor nodes, such as an attacker gaining the ability to read an eavesdropped encrypted message. There has been much research addressing the issue of providing content privacy, eg, SPINS, 6 with most efforts in this area focusing on the use of cryptographic techniques. On the other hand, context-based privacy threats focus on the context in which messages are broadcast and how information can be observed or inferred by attackers. Context is a multi-attribute concept that encompasses situational aspects of broadcast messages, including environmental and temporal information.It is often desirable for the source of sensed information to be kept private in a WSN. For example, in a military application, a soldier transmitting messages may unintentionally disclose their location, even when encryption is used. Another example is during the monitoring of endangered species where poachers may be tempted to infer the location of the animal to capture it. Real world examples include monitoring badgers 2 and the WWF's Wildlife Crime Technology Report, 7 both of which would likely benefit from a context-based security measure. In this paper, we focus on protecting the source location.Techniques that protect this source location are said to provide source location privacy (SLP). SLP is important in many application domains, though it is of utmost concern in security-critica...

Section: Resultsmentioning

confidence: 99%

Phantom walkabouts: A customisable source location privacy aware routing protocol for wireless sensor networks

Concurrency and Computation

2019

Self Cite

“…An issue with SLP routing protocol is that they require an element of redundancy [35] in order to provide SLP. Therefore, we now show that proper completing paths cannot always exist and under what circumstances a proper competing path needs to exist for an SLP routing protocol to exist.…”

Section: Existence Of Proper Competing Pathsmentioning

confidence: 99%

Quantifying Source Location Privacy Routing Performance via Divergence and Information Loss

IEEE Trans.Inform.Forensic Secur.

2022

Source location Privacy (SLP) is an important property for security critical applications deployed over a wireless sensor network. This property specifies that the location of the source of messages needs to be kept secret from an eavesdropping adversary that is able to move around the network. Most previous work on SLP has focused on developing protocols to enhance the SLP imparted to the network under various attacker models and other conditions. Other works have focused on analysing the level of SLP being imparted by a specific protocol. In this paper, we introduce the notion of a routing matrix which captures when messages are first received. We then introduce a novel approach where an optimal SLP routing matrix is derived. In this approach, the attacker's movement is modelled as a Markov chain where measures of conditional entropy and divergence are used to compare routing matrices and quantify if they provide high levels of SLP. We propose the notion of a properly competing paths that causes an attacker to divert when moving towards the source. This concept provides the basis for developing a perturbation model, similar to those used in privacy-preserving data mining. We formally prove that properly competing paths are both necessary and sufficient in ensuring the existence of an SLP-aware routing matrix and show their usage in developing an SLP-aware routing matrix. Further, we show how different SLP-aware routing matrices can be obtained through different instantiations of the framework. Those instantiations are obtained based on a notion of information loss achieved through the use of the perturbation model proposed.

“…There are two main classes of SLP-aware routing protocols: spatial and temporal [23]. The objective of a spatial SLP-aware routing protocol is to ensure that the attacker takes a path which is longer than the shortest path to reach the asset.…”

Section: Problem Statement Formalisationmentioning

confidence: 99%

“…We proposed two rules, based on message transmissions, for the transformation. We conjecture that the transformation process can be applied to other spatial SLP protocols [23] modelled as schedules, as shown in Figures 20 and 21, where two different variants of DynamicSPR were considered. As such, once the non-duty cycled SLP protocol has been modelled as a schedule, then similar transformation rules can be applied, with the difference being in the size of the windows.…”

Section: Applicability To Other Techniquesmentioning

confidence: 99%

“…Thus, this interference needs to be factored in when choosing fake sources. Removing nodes which act as a relay reduces the size of the set of potential fake sources, making it nearly impossible when the number of sources is large because there is insufficient spatial redundancy [23]. In these cases, using a temporal SLP-aware routing protocol, such as [5], is advisable.…”

Section: Multiple Sourcesmentioning

confidence: 99%

See 1 more Smart Citation

A Spatial Source Location Privacy-aware Duty Cycle for Internet of Things Sensor Networks

ACM Trans. Internet Things

Maple

2021

Self Cite

Source Location Privacy (SLP) is an important property for monitoring assets in privacy-critical sensor network and Internet of Things applications. Many SLP-aware routing techniques exist, with most striking a tradeoff between SLP and other key metrics such as energy (due to battery power). Typically, the number of messages sent has been used as a proxy for the energy consumed. Existing work (for SLP against a local attacker) does not consider the impact of sleeping via duty cycling to reduce the energy cost of an SLP-aware routing protocol. Therefore, two main challenges exist: (i) how to achieve a low duty cycle without loss of control messages that configure the SLP protocol and (ii) how to achieve high SLP without requiring a long time spent awake. In this article, we present a novel formalisation of a duty cycling protocol as a transformation process. Using derived transformation rules, we present the first duty cycling protocol for an SLP-aware routing protocol for a local eavesdropping attacker . Simulation results on grids demonstrate a duty cycle of 10%, while only increasing the capture ratio of the source by 3 percentage points, and testbed experiments on FlockLab demonstrate an 80% reduction in the average current draw.