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Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments

Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments
Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments

The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.

Inference management, Obfuscation, QoI, Quality of information, Risk of information, RoI, Value of information, VoI
1574-1192
168-187
Bisdikian, Chatschik
cdd2ccbd-cbb5-498e-8481-2f74c2fb0090
Gibson, Christopher
bb54ae94-c3be-439b-9076-f11ca79edac2
Chakraborty, Supriyo
5b69835d-c267-472d-b842-e489d5e2390a
Srivastava, Mani B.
ad46bd05-df44-4768-8278-1228808ad588
Sensoy, Murat
769b0b6a-705b-456a-ab3d-123bca9cc66a
Norman, Timothy J.
663e522f-807c-4569-9201-dc141c8eb50d
Bisdikian, Chatschik
cdd2ccbd-cbb5-498e-8481-2f74c2fb0090
Gibson, Christopher
bb54ae94-c3be-439b-9076-f11ca79edac2
Chakraborty, Supriyo
5b69835d-c267-472d-b842-e489d5e2390a
Srivastava, Mani B.
ad46bd05-df44-4768-8278-1228808ad588
Sensoy, Murat
769b0b6a-705b-456a-ab3d-123bca9cc66a
Norman, Timothy J.
663e522f-807c-4569-9201-dc141c8eb50d

Bisdikian, Chatschik, Gibson, Christopher, Chakraborty, Supriyo, Srivastava, Mani B., Sensoy, Murat and Norman, Timothy J. (2014) Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments. Pervasive and Mobile Computing, 11, 168-187. (doi:10.1016/j.pmcj.2013.08.003).

Record type: Article

Abstract

The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.

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More information

Published date: April 2014
Keywords: Inference management, Obfuscation, QoI, Quality of information, Risk of information, RoI, Value of information, VoI

Identifiers

Local EPrints ID: 492962
URI: http://eprints.soton.ac.uk/id/eprint/492962
ISSN: 1574-1192
PURE UUID: f39555f1-9172-4591-bfea-0e6cf215bd5d
ORCID for Timothy J. Norman: ORCID iD orcid.org/0000-0002-6387-4034

Catalogue record

Date deposited: 21 Aug 2024 17:03
Last modified: 22 Aug 2024 01:47

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Contributors

Author: Chatschik Bisdikian
Author: Christopher Gibson
Author: Supriyo Chakraborty
Author: Mani B. Srivastava
Author: Murat Sensoy

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