Abstract
We outline our computational framework for identity. We have a prototype web application, but this paper is a conceptual level. The interest is in identity as an equivalence relation and how information can be evidence for identity hypotheses. Our account is based on the situation theory of Barwise and Perry. We consider a (legal) identity case to be a constellation of situations, and we indicate how the structure of such a case facilitates discounting and combining evidence using Dempster-Shafer theory. Semantic Web resources are used to capture the structure of evidence as it relates to situations. We have developed OWL ontologies and use the concepts therein defined in RDF triple stores to capture case data. URIs (as used in the Semantic Web) are used for unambiguous references to individuals. We sketch a scenario that uses two biometric modalities in an uncontrolled environment and show how our framework applies. Recently, biometrics has gained the limelight as a means to identify individuals, but much else may be available for this task, including sensor data, witness reports, and data on file. To our knowledge, this is the only framework that in principle can accommodate any kind of evidence for identity. It is not an alternative to biometrics, but rather provides a way to incorporate biometrics into a larger context.
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Acknowledgments
This research is based upon work supported by the Army Research Office (Contract No. W911NF-15-1-0524).
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Mason, J., Chatterjee, P., Roy, K., Esterline, A. (2019). A Framework to Identify People in Unstructured Environments Incorporating Biometrics. In: Wang, G., Feng, J., Bhuiyan, M., Lu, R. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2019. Lecture Notes in Computer Science(), vol 11637. Springer, Cham. https://doi.org/10.1007/978-3-030-24900-7_5
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