Phantom walkabouts in wireless sensor networks

Gu, Chen; Bradbury, Matthew; Jhumka, Arshad

doi:10.1145/3019612.3019732

Cited by 5 publications

(9 citation statements)

References 26 publications

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“…For example, having the route approach the sink from a direction other than the one the source is in has been used in Phantom Routing [3] and Ring-based Routing [7]. We have also seen algorithms whose routes occasionally take the shortest path [26]. However, we have not seen delaying and grouping messages previously in providing SLP.…”

Section: Model Resultsmentioning

confidence: 99%

A Near-Optimal Source Location Privacy Scheme for Wireless Sensor Networks

Bradbury

Jhumka

2017

2017 IEEE Trustcom/BigDataSE/Icess

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Section: Model Resultsmentioning

confidence: 99%

A Near-Optimal Source Location Privacy Scheme for Wireless Sensor Networks

Bradbury

Jhumka

2017

2017 IEEE Trustcom/BigDataSE/Icess

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“…However, there is still scope to improve the nodes that are allocated to take part in the directed random walk. Phantom walkabouts was an algorithm also using a random walk technique to provide SLP . The technique used a mix of short and long random walks to achieve a higher level of SLP than phantom routing with a bounded message overhead.…”

Section: Related Workmentioning

confidence: 99%

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

Bradbury

Jhumka

2019

Concurrency and Computation

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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...

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“…However, there is still scope to improve the nodes that are allocated to take part in the directed random walk. Other algorithms use the random walk technique to address the SLP issue such as randomly selected intermediary node (RRIN) [22], random routing scheme (RRS) [23] and phantom walkabouts [24].…”

Section: Phantom Walk Techniquementioning

confidence: 99%

“…Phantom walkabouts is an algorithm using a random walk technique to provide SLP [24]. The new technique, which uses a mix of short and long random walks, achieves a higher level of SLP than phantom routing with a bounded message overhead.…”

Section: Phantom Walkaboutsmentioning

confidence: 99%