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Collusion-Secure Watermarking for Sequential Data | | Arif Yilmaz
; Erman Ayday
; | | Date: |
3 Aug 2017 | | Abstract: | In this work, we address the liability issues that may arise due to
unauthorized sharing of personal data. We consider a scenario in which an
individual shares his sequential data (such as genomic data or location
patterns) with several service providers (SPs). In such a scenario, if his data
is shared with other third parties without his consent, the individual wants to
determine the service provider that is responsible for this unauthorized
sharing. To provide this functionality, we propose a novel optimization-based
watermarking scheme for sharing of sequential data. Thus, in the case of an
unauthorized sharing of sensitive data, the proposed scheme can find the source
of the leakage by checking the watermark inside the leaked data. In particular,
the proposed schemes guarantees with a high probability that (i) the SP that
receives the data cannot understand the watermarked data points, (ii) when more
than one SPs aggregate their data, they still cannot determine the watermarked
data points, (iii) even if the unauthorized sharing involves only a portion of
the original data or modified data (to damage the watermark), the corresponding
SP can be kept responsible for the leakage, and (iv) the added watermark is
compliant with the nature of the corresponding data. That is, if there are
inherent correlations in the data, the added watermark still preserves such
correlations. Watermarking typically means changing certain parts of the data,
and hence it may have negative effects on data utility. The proposed scheme
also minimizes such utility loss while it provides the aforementioned security
guarantees. Furthermore, we conduct a case study of the proposed scheme on
genomic data and show the security and utility guarantees of the proposed
scheme. | | Source: | arXiv, 1708.1023 | | Services: | Forum | Review | PDF | Favorites | |
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