Publication Details
Title: Semantic Computing and Privacy: A Case Study Using Inferred Geo-Location
Author: G. Friedland and J. Choi
Bibliographic Information: International Journal of Semantic Computing, Vol. 5, No. 1, pp. 79-93. Also Best Poster in the Electrical and Computer Science and Engineering Track at the Korean Student Technical and Leadership Conference, Chicago, Illinois, March 2012. DOI: 10.1142/S1793351X11001171
Date: March 2011
Research Area: Audio and Multimedia, Networking and Security
Type: Article in journal or magazine
PDF: http://www.icsi.berkeley.edu/pubs/speech/semanticcomputing11.pdf
Overview:
This paper presents an experiment that allows the inference over data published in social networks, resulting in a potentially severe privacy leak, more specifically the inference of geo-location resulting in the potential of cybercasing attacks. We present an algorithm that allows the inference of the geo-location of YouTube and Flickr videos based on the tag descriptions. Using the locations, we find people where we can infer both the home address as well as the fact that they are currently on vacation, which makes them potential targets for burglary. By doing so we repeat an experiment from the literature that was originally meant to show the potential dangers of geo-tagging but replacing the geo-tags with Semantic Computing methods. We conclude that the only way to tackle potential threats like this is for researchers to develop an enhanced notion of privacy for Semantic Computing. Keywords: Semantic computing; social computing; privacy.
Acknowledgements:
This work was partially supported by funding provided to ICSI through National Science Foundation grant CNS : 1065240 (“Understanding and Managing the Impact of Global Inference on Online Privacy”) and also through NGA NURI grant #HM11582-10-1-0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of either the National Science Foundation or the NGA.
Bibliographic Reference:
G. Friedland and J. Choi. Semantic Computing and Privacy: A Case Study Using Inferred Geo-Location. International Journal of Semantic Computing, Vol. 5, No. 1, pp. 79-93. Also Best Poster in the Electrical and Computer Science and Engineering Track at the Korean Student Technical and Leadership Conference, Chicago, Illinois, March 2012. DOI: 10.1142/S1793351X11001171, March 2011
Author: G. Friedland and J. Choi
Bibliographic Information: International Journal of Semantic Computing, Vol. 5, No. 1, pp. 79-93. Also Best Poster in the Electrical and Computer Science and Engineering Track at the Korean Student Technical and Leadership Conference, Chicago, Illinois, March 2012. DOI: 10.1142/S1793351X11001171
Date: March 2011
Research Area: Audio and Multimedia, Networking and Security
Type: Article in journal or magazine
PDF: http://www.icsi.berkeley.edu/pubs/speech/semanticcomputing11.pdf
Overview:
This paper presents an experiment that allows the inference over data published in social networks, resulting in a potentially severe privacy leak, more specifically the inference of geo-location resulting in the potential of cybercasing attacks. We present an algorithm that allows the inference of the geo-location of YouTube and Flickr videos based on the tag descriptions. Using the locations, we find people where we can infer both the home address as well as the fact that they are currently on vacation, which makes them potential targets for burglary. By doing so we repeat an experiment from the literature that was originally meant to show the potential dangers of geo-tagging but replacing the geo-tags with Semantic Computing methods. We conclude that the only way to tackle potential threats like this is for researchers to develop an enhanced notion of privacy for Semantic Computing. Keywords: Semantic computing; social computing; privacy.
Acknowledgements:
This work was partially supported by funding provided to ICSI through National Science Foundation grant CNS : 1065240 (“Understanding and Managing the Impact of Global Inference on Online Privacy”) and also through NGA NURI grant #HM11582-10-1-0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of either the National Science Foundation or the NGA.
Bibliographic Reference:
G. Friedland and J. Choi. Semantic Computing and Privacy: A Case Study Using Inferred Geo-Location. International Journal of Semantic Computing, Vol. 5, No. 1, pp. 79-93. Also Best Poster in the Electrical and Computer Science and Engineering Track at the Korean Student Technical and Leadership Conference, Chicago, Illinois, March 2012. DOI: 10.1142/S1793351X11001171, March 2011