Privacy Sensitive Location Information Systems in Smart Buildings

Boyer, J.P.; Tan, Kaijun; Gunter, Carl A.

doi:10.1007/11734666_12

Cited by 10 publications

(14 citation statements)

References 6 publications

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“…Palen and Dourish [17] extend privacy regulation theory to the consideration of the design and analysis of information technology. Similarly, Boyer et al [3] argued that a single privacy model cannot be applied across applications, Dourish and Grinter [6] link the definition of security with the dynamic aspect of the privacy process, and Hong and Landay [9], state "the point is that, rather than being a single monolithic concept, privacy is a fluid and malleable notion with a range of trust levels and needs (pg. 92)."…”

Section: Privacy In Ubiquitous Computingmentioning

confidence: 97%

“…using an observers authorisation level [18], an observed person's preferences for a given observer [3], a user's pre-defined preferences [7], or a users requested privacy level [20].…”

Section: Privacy Sensitive Ubiquitous Computing Applicationsmentioning

confidence: 99%

“…the observer or occupant). In certain applications, privacy is implemented by default [18,7,3]. However, other applications assess the context in order to determine whether or not privacy measures should be implemented [20,15].…”

Section: Introductionmentioning

confidence: 99%

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Privacy and the access of information in a smart house environment

Moncrieff

Venkatesh

West

2007

Proceedings of the 15th ACM International Conference on Multimedia

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In this paper we present a framework for addressing privacy issues raised by the monitoring of assisted living smart house environments. In home environments, the conflict between the goals of the surveillance, and the private nature of the home, raises the issue of occupant privacy. This issue needs to be addressed if applications are to be accepted by the occupant. We identify four key properties required for the design of privacy sensitive ubiquitous computing applications. Subsequently, we develop a dynamic and flexible method for implementing privacy measures through controlling access to data, and an interface to provide feedback to the occupant, enabling them to control the implemented privacy measures. We form a generic framework for implementing privacy sensitive ubiquitous computing applications based on previous applications within the field. This framework was then extended and used to develop a specific framework for a privacy sensitive smart house. The approach proposed in the framework dynamically applies privacy measures to multi-modal data according to the situation, or context, of the environment. We further test an implementation of the privacy measures, and detail methods to implement feedback and control. The approach aims to decrease the invasiveness of the surveillance, while retaining the purpose of the assisted living environment.

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Section: Privacy In Ubiquitous Computingmentioning

confidence: 97%

“…using an observers authorisation level [18], an observed person's preferences for a given observer [3], a user's pre-defined preferences [7], or a users requested privacy level [20].…”

Section: Privacy Sensitive Ubiquitous Computing Applicationsmentioning

confidence: 99%

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Privacy and the access of information in a smart house environment

Moncrieff

Venkatesh

West

2007

Proceedings of the 15th ACM International Conference on Multimedia

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“…The number of states of M IDM A red N can be determined using the notion of multiset (see [7] for more details about multisets and other enumerative problems). Despite its apparent complexity, the proposed modeling approach remains scalable since we consider only instrumented apartments or houses and not a whole smart building (like for instance in [8]). Consequently, both the number of zones Z and the number of inhabitants N remain small.…”

Section: Model Reductionmentioning

confidence: 99%

A Discrete event model for multiple inhabitants location tracking

Danancher

Lesage

Litz

et al. 2013

2013 IEEE International Conference on Automation Science and Engineering (CASE)

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Abstract-Smart Home technologies are aiming to improve the comfort and safety of the inhabitants into their houses. To achieve this goal, online indoor location tracking of the inhabitants is often used to monitor the air conditioning, to detect dangerous situations and for many other applications. In this paper, it is proposed an approach to build a model allowing dynamic tracking of several persons in their house. A method to construct such a model by using finite automata and Discrete Event System (DES) paradigms is presented. An approach to reduce the size of the model is also introduced. Finally, an efficient algorithm for location tracking is proposed. For the sake of better understanding, an illustrative example is used throughout the paper.

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“…By using information theory and hidden Markov models, the authors in [21] provide a novel privacy-utility tradeoff of smart meter data. Besides the smart grid, the research has also been devoted to study M user privacy of intelligent transportation systems [13] and smart buildings [4], [18]. However, this set of work does not explicitly consider physical dynamics.…”

Section: Introductionmentioning

confidence: 99%

On confidentiality preserving monitoring of linear dynamic networks against inference attacks

Zhu

Lü

2015

2015 American Control Conference (ACC)

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Distributed information sharing in dynamic networks is ubiquitous. It raises the concern that confidential information of dynamic networks could be leaked to malicious entities and further exploited in direct attacks. In this paper, we formulate the problem of competitive confidentiality preserving monitoring of linear dynamic networks against inference attacks. We show that the unstructured 0 minimization is NPhard. We then provide a SDP equivalence for the structured 2 minimization.

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Privacy Sensitive Location Information Systems in Smart Buildings

Cited by 10 publications

References 6 publications

Privacy and the access of information in a smart house environment

Privacy and the access of information in a smart house environment

A Discrete event model for multiple inhabitants location tracking

On confidentiality preserving monitoring of linear dynamic networks against inference attacks

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