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.
- Altman, I. 1975. The Environment and Social Behavior: Privacy, Personal Space, Territory and Crowding. Brooks/Cole Publishing Co., Inc., Monterey, CA.Google Scholar
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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.Google Scholar
- Daubechies, I. 1992. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, Philadelphia, PA. Google Scholar
Digital Library
- Deller, J. R., Proakis, J. G., and Hansen, J. H. 1993. Discrete Time Processing of Speech Signals. Prentice Hall PTR, Upper Saddle River, NJ. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Cross Ref
- 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.Google Scholar
- 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.Google Scholar
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- 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.Google Scholar
- 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.Google Scholar
- 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. Google Scholar
Digital Library
- Rabiner, L. and Juang, B. 1978. Digital Processing of Speech Signals. Signal Processing Series. Prentice Hall Press, New Jersey.Google Scholar
- 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. Google Scholar
Digital Library
- 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.Google Scholar
- 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. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
- Wilson, D. H. 2005. Assistive intelligent environments for automatic health monitoring. Ph.D. thesis, Robotics Institute, Carnegie Mellon University. Google Scholar
Digital Library
- Witten, I. H. and Frank, E. 2000. Data Mining: Practical machine learning tools with Java implementations. Morgan Kaufmann. Google Scholar
Digital Library
- 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. Google Scholar
Digital Library
Index Terms
Dynamic privacy assessment in a smart house environment using multimodal sensing
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