Semantic Computing and Privacy: A Case Study Using Inferred Geo-Location

TitleSemantic Computing and Privacy: A Case Study Using Inferred Geo-Location
Publication TypeJournal Article
Year of Publication2011
AuthorsFriedland, G., & Choi J.
Published inInternational Journal of Semantic Computing
Other Numbers3283
Keywordsprivacy, Semantic computing, social computing

This paper presents an experiment that allows the inference over data published in socialnetworks, resulting in a potentially severe privacy leak, more specifically the inference ofgeo-location resulting in the potential of cybercasing attacks. We present an algorithmthat allows the inference of the geo-location of YouTube and Flickr videos based onthe tag descriptions. Using the locations, we find people where we can infer both thehome address as well as the fact that they are currently on vacation, which makes thempotential targets for burglary. By doing so we repeat an experiment from the literaturethat was originally meant to show the potential dangers of geo-tagging but replacing thegeo-tags with Semantic Computing methods. We conclude that the only way to tacklepotential threats like this is for researchers to develop an enhanced notion of privacy forSemantic Computing.


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 Notes

International Journal of Semantic Computing, Vol. 5, No. 1, pp. 79-93. DOI: 10.1142/S1793351X11001171

Abbreviated Authors

G. Friedland and J. Choi

ICSI Research Group

Networking and Security

ICSI Publication Type

Article in journal or magazine