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Proposal of Non-invasive Fingerprint Age Determination to Improve Data Privacy Management in Police Work from a Legal Perspective Using the Example of Germany

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Data Privacy Management and Autonomous Spontaneous Security (DPM 2012, SETOP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7731))

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Abstract

Innovation in sensors and pattern recognition technologies impacts on our society. Recent improvements in capturing techniques allow for the application of high-resolution contactless image sensors to the lifting of latent fingerprints, potentially replacing classical contact based techniques such as powdering and sticky tape lifting in the future. This technology might help police authorities to identify criminals, but it also poses privacy concerns due to its ability to capture large amounts of fingerprints. Therefore, one has to give special consideration to data privacy management. One way of promoting data privacy could be to determine the age of fingerprints in advance and to not capture fingerprints left at times irrelevant for a crime. Another way could be to determine the age of fingerprints in parallel to the investigation and securely delete fingerprint data as soon as it is found to be of age different to the crime. To this end, we explore the possible future technology of fingerprint age determination and its use for data privacy protection in a repressive application scenario at the crime scene as well as a preventive one at the airport. This will be analyzed from a technical-legal point of view in order to promote legal criteria of the German and European privacy and data protection laws.

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Merkel, R., Pocs, M., Dittmann, J., Vielhauer, C. (2013). Proposal of Non-invasive Fingerprint Age Determination to Improve Data Privacy Management in Police Work from a Legal Perspective Using the Example of Germany. In: Di Pietro, R., Herranz, J., Damiani, E., State, R. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2012 2012. Lecture Notes in Computer Science, vol 7731. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35890-6_5

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  • DOI: https://doi.org/10.1007/978-3-642-35890-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35889-0

  • Online ISBN: 978-3-642-35890-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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