Svyatoslav Voloshynovskiy

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Watermarking is a potential method for protection of ownership rights on digital audio, image, and video data. Benchmarks are used to evaluate the performance of different watermarking algorithms. For image watermarking, the Stirmark package is the most popular benchmark, and the best current algorithms perform well against it. However, results obtained by(More)
In recent years, content identification based on digital fingerprinting attracts a lot of attention in different emerging applications. At the same time, the theoretical analysis of digital fingerprinting systems for finite length case remains an open issue. Additionally, privacy leaks caused by fingerprint storage, distribution and sharing in a public(More)
SIFT descriptors are broadly used in various emerging applications. In recent years, these descriptors were deployed in compressed and binarized forms due to the computational complexity, storage, security and privacy cost incurred by working on real data. At the same time, the theoretical analysis of SIFT feature performance in different applications(More)
The upper capacity bound of a brain-computer interface (BCI) is determined using a model based on Shannon channel theory. This capacity is compared with all bit-rate definitions used in the BCI community (Nykopp, Farwell and Donchin, Wolpaw et al); assumptions underlying those definitions and their limitations are discussed. Capacity estimates using Wolpaw(More)
Identification of contents or objects based on some data that are stored/distributed in public domain is required in various applications. At the same time, these data should not reveal any information about original content or object that may be missused in terms of privacy leakage. We consider a privacy protection strategy based on reliable components of(More)
In this paper, we analyze the reversibility of data hiding techniques based on random binning as a by-product of pure message communications. We demonstrate the capabilities of unauthorized users to perform hidden data removal using solely a signal processing approach based on optimal estimation as well as consider reversibility on the side of authorized(More)
In this paper, we extend the results for optimal transmission of the Gaussian channel state via the state-dependent channels to the communications of the Laplacian data. We derive a minimum mean square estimate (MMSE) of the stationary independent identically (i.i.d.) distributed Laplacian channel state corrupted by an additive white Gaussian noise (AWGN)(More)
Many algorithms for protein and peptide identification from Tandem Mass Spectrometry (MS/MS) data have been published. The majority of such methods are based on sequence or spectral database search: experimental spectra are matched to theoretical spectra characterizing known peptide sequences. Hits define candidate peptides. In this context, the development(More)
In this paper, we extend a traditional robust data-hiding set-up with host state at the encoder to a case when a partial side information about host statistics is also available at the decoder. We demonstrate that the knowledge of host statistics at the decoder can relax the critical requirements of random binning-based methods concerning attack channel(More)
The identification problem in modern applications such as biometrics and brand protection is concerned with new requirements to privacy and runtime-complexity besides the classical demand for accuracy or the performance in terms of identification error. Hence, previous work is extended by coupling the existing model of identification systems to a model from(More)