Collusion-secure watermarking for sequential data
Author(s)
Advisor
Ayday, ErmanDate
2017-09Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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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 nd 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, 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
e ects 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.