  Database fingerprinting has been widely used to discourage unauthorized
redistribution of data by providing means to identify the source of data
leakages. However, there is no fingerprinting scheme aiming at achieving
liability guarantees when sharing genomic databases. Thus, we are motivated to
fill in this gap by devising a vanilla fingerprinting scheme specifically for
genomic databases. Moreover, since malicious genomic database recipients may
compromise the embedded fingerprint by launching effective correlation attacks
which leverage the intrinsic correlations among genomic data (e.g., Mendel's
law and linkage disequilibrium), we also augment the vanilla scheme by
developing mitigation techniques to achieve robust fingerprinting of genomic
databases against correlation attacks.
  We first show that correlation attacks against fingerprinting schemes for
genomic databases are very powerful. In particular, the correlation attacks can
distort more than half of the fingerprint bits by causing a small utility loss
(e.g.,database accuracy and consistency of SNP-phenotype associations measured
via p-values). Next, we experimentally show that the correlation attacks can be
effectively mitigated by our proposed mitigation techniques. We validate that
the attacker can hardly compromise a large portion of the fingerprint bits even
if it pays a higher cost in terms of degradation of the database utility. For
example, with around 24% loss in accuracy and 20% loss in the consistency of
SNP-phenotype associations, the attacker can only distort about 30% fingerprint
bits, which is insufficient for it to avoid being accused. We also show that
the proposed mitigation techniques also preserve the utility of the shared
genomic databases.
