research-article

Dynamic privacy assessment in a smart house environment using multimodal sensing

Authors:

Simon Moncrieff,

Svetha Venkatesh,

Geoff WestAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 5, Issue 2

Article No.: 10, Pages 1 - 29

https://doi.org/10.1145/1413862.1413863

Published: 20 November 2008 Publication History

Abstract

Surveillance applications in private environments such as smart houses require a privacy management policy if such systems are to be accepted by the occupants of the environment. This is due to the invasive nature of surveillance, and the private nature of the home. In this article, we propose a framework for dynamically altering the privacy policy applied to the monitoring of a smart house based on the situation within the environment. Initially the situation, or context, within the environment is determined; we identify several factors for determining environmental context, and propose methods to quantify the context using audio and binary sensor data. The context is then mapped to an appropriate privacy policy, which is implemented by applying data hiding techniques to control access to data gathered from various information sources. The significance of this work lies in the examination of privacy issues related to assisted-living smart house environments. A single privacy policy in such applications would be either too restrictive for an observer, for example, a carer, or too invasive for the occupants. We address this by proposing a dynamic method, with the aim of decreasing the invasiveness of the technology, while retaining the purpose of the system.

References

[1]

Altman, I. 1975. The Environment and Social Behavior: Privacy, Personal Space, Territory and Crowding. Brooks/Cole Publishing Co., Inc., Monterey, CA.

[2]

Bellotti, V. and Sellen, A. 1993. Design for privacy in ubiquitous computing environments. In Proceedings of the 3rd European Conference on Computer-Supported Cooperative Work (ECSCW'93). Kluwer Academic Publishers, Norwell, MA, 77--92.

Digital Library

[3]

Boyer, J. P., Tan, K., and Gunter, C. A. 2006. Privacy sensitive location information systems in smart buildings. In Proceedings of the 3rd International Conference for Security in Pervasive Computing. Springer Berlin, York, England.

Digital Library

[4]

Chen, J., Kam, A. H., Zhang, J., Liu, N., and Shue, L. 2005. Bathroom activity monitoring based on sound. In Pervasive Comput. Springer Berlin, Munich, Germany, 47--61.

Digital Library

[5]

Das, S. and Cook, D. J. 2004. Health monitoring in an agent-based smart home. In Proceedings of the International Conference on Smart Homes and Health Telematics (ICOST). IOS Press, Singapore.

[6]

Daubechies, I. 1992. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, Philadelphia, PA.

Digital Library

[7]

Deller, J. R., Proakis, J. G., and Hansen, J. H. 1993. Discrete Time Processing of Speech Signals. Prentice Hall PTR, Upper Saddle River, NJ.

Digital Library

[8]

Dufaux, F. and Ebrahimi, T. 2006. Scrambling for video surveillance with privacy. In Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06). IEEE Computer Society, Washington, DC, 160--166.

Digital Library

[9]

Ellis, D. P. and Lee, K. 2004. Minimal-impact audio-based personal archives. In Proceedings of the 1st ACM Workshop on Continuous Archival and Retrieval of Personal Experiences. ACM Press, New York, 39--47.

Digital Library

[10]

Fidaleo, D. A., Nguyen, H., and Trivedi, M. 2004. The networked sensor tapestry (nest): a privacy enhanced software architecture for interactive analysis of data in video-sensor networks. In Proceedings of the ACM 2nd International Workshop on Video Surveillance & Sensor Networks (VSSN '04). ACM, New York, 46--53.

Digital Library

[11]

Helal, S., Winkler, B., Lee, C., Kaddoura, Y. Ran, L., Giraldo, C., Kuchibhotla, S., and Mann, W. 2003. Enabling location-aware pervasive computing applications for the edlerly. In Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PERCOM'03). IEEE Computer Society, Washington, DC, 531--536.

Digital Library

[12]

Hong, D., Yuan, M., and Shen, V. Y. 2005. Dynamic privacy management: a plug-in service for the middleware in pervasive computing. In 7th International Conference on Human Computer Interaction with Mobile Devices; Services (MobileHCI'05). Vol. 111. ACM Press, New York, NY, 1--8.

Digital Library

[13]

Hong, J. I. and Landay, J. A. 2004. An architecture for privacy-sensitive ubiquitous computing. In Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services (MobiSys'04). ACM Press, New York, 177--189.

Digital Library

[14]

Lederer, S., Hong, I., Dey, K., and Landay, A. 2004. Personal privacy through understanding and action: five pitfalls for designers. Personal Ubiquitous Comput. 8, 6, 440--454.

[15]

Martinez-Ponte, I., Desurmont, X., Meessen, J., and Delaigle, J.-F. 2005. Robust human face hiding ensuring privacy. In Proceedings of the Workshop on the Integration of Knowledge, Semantics and Digital Media Technology (WIAMIS'05). SPIE, Montreux, Switzerland.

[16]

Moncrieff, S., Venkatesh, S., and West, G. 2007a. Dynamic privacy in a smart house environment. In Proceedings of the IEEE International Conference on Multimedia and Expo. IEEE Computer Society, 2034--2037.

[17]

Moncrieff, S., Venkatesh, S., and West, G. 2007b. On-line audio background determination for complex audio environments. ACM Trans. Multimed. Comput. Comm. Appl. (TOMCCAP) 3, 2 (May), 1--30.

Digital Library

[18]

Moncrieff, S., Venkatesh, S., and West, G. 2007c. Privacy and the access of information in a smart house environment. In ACM Multimedia 2007. ACM, 671--680.

Digital Library

[19]

Moncrieff, S. Venkatesh, S., West, G., and Greenhill, S. 2007d. Multi-modal emotive computing in a smart house environment. Pervasive and Mobile Computing, Special Issue on Design and Use of Smart Environments 3, 2 74--94.

Digital Library

[20]

Neustaedter, C. and Greenberg, S. 2003. The design of a context-aware home media space for balancing privacy and awareness. In Proceedings of the 5th International Conference on Ubiquitous Computing. Springer Berlin, Seattle,WA, 297--314.

[21]

Nixon, P. A., Wagealla, W., English, C., and Terzis, S. 2004. Smart Environments: Technology, Protocols, and Applications. Wiley, Arlington, TX, Chapter Security, Privacy and Trust Issues in Smart Environments, 249--270.

[22]

Palen, L. and Dourish, P. 2003. Unpacking “privacy” for a networked world. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI03). ACM, 129--136.

Digital Library

[23]

Rabiner, L. and Juang, B. 1978. Digital Processing of Speech Signals. Signal Processing Series. Prentice Hall Press, New Jersey.

[24]

Senior, A., Pankanti, S., Hampapur, A., Brown, L., Tian, Y.-L., and Ekin, A. 2005. Enabling video privacy through computer vision. IEEE Security and Privacy 3, 3, 50--57.

Digital Library

[25]

Stauffer, C. and Grimson, W. 1999. Adaptive background mixture models for real-time tracking. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1999. Vol. 2. IEEE Computer Society, Fort Collins, CO USA, 246--252.

[26]

West, G., Greenhill, S., and Venkatesh, S. 2005. A probabilistic approach to the anxious home for activity monitoring. In Proceedings of the 29th Annual International Computer Software and Applications Conference (COMPSAC'05) Volume 1. IEEE Computer Society. 335--340.

Digital Library

[27]

Wickramasuriya, J., Alhazzazi, M., Datt, M., Mehrotra, S., and Venkatasubramanian, N. 2004. Privacy protecting data collection in media spaces. In Proceedings of the 12th annual ACM international conference on Multimedia (MULTIMEDIA '04). ACM, New York, 48--55.

Digital Library

[28]

Wilson, D. H. 2005. Assistive intelligent environments for automatic health monitoring. Ph.D. thesis, Robotics Institute, Carnegie Mellon University.

Digital Library

[29]

Witten, I. H. and Frank, E. 2000. Data Mining: Practical machine learning tools with Java implementations. Morgan Kaufmann.

Digital Library

[30]

Zhang, T. and Jay Kuo, C.-C. 1999. Hierarchical classification of audio data for archiving and retrieving. In Proceedings of the IEEE International Conference Acoustics, Speech, and Signal Processing (ICASSP'99). IEEE Computer Society, Washington, 3001--3004.

Digital Library

Cited By

Wang YLiu SLi LZhou WLi H(2024)SwinShadow: Shifted Window for Ambiguous Adjacent Shadow DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/368880320:11(1-20)Online publication date: 27-Aug-2024
https://dl.acm.org/doi/10.1145/3688803
Owens OBeer JLeonard MSudduth BBurton LWu X(2024)(Re)Defining Smart Home Through an HCI Perspective: A Systematic Review of over Two Decades of Smart Home Conceptualization and ResearchInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2437112(1-24)Online publication date: 13-Dec-2024
https://doi.org/10.1080/10447318.2024.2437112
Bagheri S(2024)Who Are the Users of Smart Homes? Surveillance in Domestic IoT ContextsPrivacy Symposium 202410.1007/978-3-031-76265-9_7(141-164)Online publication date: 27-Nov-2024
https://doi.org/10.1007/978-3-031-76265-9_7
Show More Cited By

Index Terms

Dynamic privacy assessment in a smart house environment using multimodal sensing
1. Applied computing

Recommendations

Privacy and the access of information in a smart house environment
MM '07: Proceedings of the 15th ACM international conference on Multimedia

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 ...
Multi-modal emotive computing in a smart house environment

We determine hazards within a smart house environment using an emotive computing framework. Representing a hazardous situation as an abnormal activity, we model normality using the concept of anxiety, using an agent based probabilistic approach. ...
Dynamic privacy management: a plug-in service for the middleware in pervasive computing
MobileHCI '05: Proceedings of the 7th international conference on Human computer interaction with mobile devices & services

Context-aware applications can better meet users' needs when sensing agents installed in the environment automatically provide input relevant to the application. However, this non-intrusive context usage may cause privacy concerns since sensitive user ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 5, Issue 2

November 2008

187 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/1413862

Issue’s Table of Contents

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 November 2008

Accepted: 01 March 2008

Revised: 01 March 2008

Received: 01 November 2007

Published in TOMM Volume 5, Issue 2

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Australian Research Council

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

36
Total Citations
View Citations
1,278
Total Downloads

Downloads (Last 12 months)15
Downloads (Last 6 weeks)1

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Wang YLiu SLi LZhou WLi H(2024)SwinShadow: Shifted Window for Ambiguous Adjacent Shadow DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/368880320:11(1-20)Online publication date: 27-Aug-2024
https://dl.acm.org/doi/10.1145/3688803
Owens OBeer JLeonard MSudduth BBurton LWu X(2024)(Re)Defining Smart Home Through an HCI Perspective: A Systematic Review of over Two Decades of Smart Home Conceptualization and ResearchInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2437112(1-24)Online publication date: 13-Dec-2024
https://doi.org/10.1080/10447318.2024.2437112
Bagheri S(2024)Who Are the Users of Smart Homes? Surveillance in Domestic IoT ContextsPrivacy Symposium 202410.1007/978-3-031-76265-9_7(141-164)Online publication date: 27-Nov-2024
https://doi.org/10.1007/978-3-031-76265-9_7
Okaba MTuncer T(2021)An automated location detection method in multi-storey buildings using environmental sound classification based on a new center symmetric nonlinear pattern: CS-LBlock-PatAutomation in Construction10.1016/j.autcon.2021.103645125(103645)Online publication date: May-2021
https://doi.org/10.1016/j.autcon.2021.103645
Langheinrich MSchaub F(2018)Privacy in Mobile and Pervasive ComputingSynthesis Lectures on Mobile and Pervasive Computing10.2200/S00882ED1V01Y201810MPC01310:1(1-139)Online publication date: 3-Dec-2018
https://doi.org/10.2200/S00882ED1V01Y201810MPC013
Bexheti AFedosov AElhart ILangheinrich MBailie LOliver N(2018)MemstoneProceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services10.1145/3229434.3229477(1-13)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1145/3229434.3229477
Schaub F(2018)Context-Adaptive Privacy MechanismsHandbook of Mobile Data Privacy10.1007/978-3-319-98161-1_13(337-372)Online publication date: 27-Oct-2018
https://doi.org/10.1007/978-3-319-98161-1_13
Kim SKo IKim S(2017)Quality of Private Information (QoPI) model for effective representation and prediction of privacy controls in mobile computingComputers and Security10.1016/j.cose.2017.01.00266:C(1-19)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.cose.2017.01.002
Pfeiffer CSanchez VSkeie N(2016)A Discrete Event Oriented Framework for a Smart House Behavior Monitor System2016 12th International Conference on Intelligent Environments (IE)10.1109/IE.2016.26(119-123)Online publication date: Sep-2016
https://doi.org/10.1109/IE.2016.26
You CChen YCheng W(2016)SocialCRCPervasive and Mobile Computing10.1016/j.pmcj.2015.07.00625:C(67-87)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1016/j.pmcj.2015.07.006
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents