Multiple Target Localisation in Sensor Networks with Location Privacy

Roughan, Matthew; Arnold, J.

doi:10.1007/978-3-540-73275-4_9

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Many of them [15,30,49] propose solutions that protect the measures in consensus networks by introducing in the rst step a random noise that decreases during the protocol so that a consensus close to the correct one is reached. Other works in privacy preserving data fusion were addressed in [56,57]. In these works, the authors use additive blinding or secret sharing to estimate the position of one or more targets, by computing the average of the measurements of multiple sensors.…”

Section: Contributionmentioning

confidence: 99%

Odin

Ambrosin

Braca

Conti

et al. 2017

ACM Trans. Internet Technol.

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The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of the Internet of Things (IoT) to develop new services and improve citizens’ quality of life. Sensors and smart devices generate large amounts of measurement data from sensing the environment, which is used to enable services such as control of power consumption or traffic density. To deal with such a large amount of information and provide accurate measurements, service providers can adopt information fusion, which given the decentralized nature of urban deployments can be performed by means of consensus algorithms. These algorithms allow distributed agents to (iteratively) compute linear functions on the exchanged data, and take decisions based on the outcome, without the need for the support of a central entity. However, the use of consensus algorithms raises several security concerns, especially when private or security critical information is involved in the computation. In this article we propose ODIN, a novel algorithm allowing information fusion over encrypted data. ODIN is a privacy-preserving extension of the popular consensus gossip algorithm, which prevents distributed agents from having direct access to the data while they iteratively reach consensus; agents cannot access even the final consensus value but can only retrieve partial information (e.g., a binary decision). ODIN uses efficient additive obfuscation and proxy re-encryption during the update steps and garbled circuits to make final decisions on the obfuscated consensus. We discuss the security of our proposal and show its practicability and efficiency on real-world resource-constrained devices, developing a prototype implementation for Raspberry Pi devices.

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Section: Contributionmentioning

confidence: 99%

Odin

Ambrosin

Braca

Conti

et al. 2017

ACM Trans. Internet Technol.

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“…Related works in this area include [23], which addresses the issue of privacy when fusing data coming from sensors that are assigned to multiple event detection tasks, and [20], which describes a data dissemination technique to ensure that the locations of sensors in the network are not learned by an enemy.…”

Section: Related Workmentioning

confidence: 99%

Detection and Localization Sensor Assignment with Exact and Fuzzy Locations

Rowaihy

Johnson

Pizzocaro

et al. 2009

Distributed Computing in Sensor Systems

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Abstract. Sensor networks introduce new resource allocation problems in which sensors need to be assigned to the tasks they best help. Such problems have been previously studied in simplified models in which utility from multiple sensors is assumed to combine additively. In this paper we study more complex utility models, focusing on two particular applications: event detection and target localization. We develop distributed algorithms to assign directional sensors of different types to multiple simultaneous tasks using exact location information. We extend our algorithms by introducing the concept of fuzzy location which may be desirable to reduce computational overhead and/or to preserve location privacy. We show that our schemes perform well using both exact or fuzzy location information.

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“…Some approaches allow nodes to deliver data, while protecting location information with pseudonyms, since tracking a data source without its real identity is more difficult [49]. Other approaches achieve similar goals with physical measurements [50].…”

Section: Confidentiality Integrity Availabilitymentioning

confidence: 99%

Security software engineering in wireless sensor networks

Platon¹,

Sei²

2008

Prog. Inform.

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The engineering of security is an essential discipline in software engineering. It requires one to embrace a holistic approach, as any weakness along the engineering process of the system may lead to future security breaches. It is in general difficult to achieve and becomes particularly acute in wireless sensor networks, owing to the stringent limitations in communication and computational power. We survey the current state of the art on this topic and set forth issues that require further study. The analysis of current work covers general security issues of wireless sensor network research and discusses the present achievements for engineering security with regards to earlier surveys in this domain. We also cover security capabilities of major implementation platforms, namely TinyOS and Sun SPOT TM , and present available and required mechanisms that will become essential for software engineers.

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Multiple Target Localisation in Sensor Networks with Location Privacy

Cited by 5 publications

References 10 publications

Odin

Odin

Detection and Localization Sensor Assignment with Exact and Fuzzy Locations

Security software engineering in wireless sensor networks

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