KEYWORDS: Digital watermarking, Sensors, Binary data, Information security, Receivers, Signal detection, Modulation, Distortion, Detection and tracking algorithms, Statistical analysis
Zero-knowledge watermark detectors presented to date are based on a linear correlation between the asset features
and a given secret sequence. This detection function is susceptible of being attacked by sensitivity attacks, for
which zero-knowledge does not provide protection.
In this paper, an efficient zero-knowledge version of the Generalized Gaussian Maximum Likelihood (ML)
detector is introduced. The inherent robustness that this detector presents against sensitivity attacks, together
with the security provided by the zero-knowledge protocol that conceals the keys that could be used to remove
the watermark or to produce forged assets, results in a robust and secure protocol.
Two versions of the zero-knowledge detector are presented; the first one makes use of two new zero-knowledge
proofs for modulus and square root calculation; the second is an improved version applicable when the spreading
sequence is binary, and it has minimum communication complexity.
Completeness, soundness and zero-knowledge properties of the developed protocols are proved, and they are
compared with previous zero-knowledge watermark detection protocols in terms of receiver operating characteristic,
resistance to sensitivity attacks and communication complexity.
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