Browsing by Subject "Watermarking"

Now showing 1 - 5 of 5

Open Access
Privacy preserving and robust watermarking on sequential genome data using belief propagation and local differential privacy
(2020-08) Öksüz, Abdullah Çağlar
Genome data is a subject of study for both biology and computer science since the start of Human Genome Project in 1990. Since then, genome sequencing for medical and social purposes becomes more and more available and aﬀordable. For research, these genome data can be shared on public websites or with service providers. However, this sharing process compromises the privacy of donors even under partial sharing conditions. In this work, we mainly focus on the liability aspect ensued by unauthorized sharing of these genome data. One of the techniques to address the liability issues in data sharing is watermarking mechanism. In order to detect malicious correspondents and service providers (SPs) -whose aim is to share genome data without individuals’ consent and undetected-, we propose a novel watermarking method on sequential genome data using belief propagation algorithm. In our method, we have three criteria to satisfy. (i) Embedding robust watermarks so that the malicious adversaries can not temper the watermark by modiﬁcation and are identiﬁed with high probability (ii) Achieving -local diﬀerential privacy in all data sharings with SPs and (iii) Preserving the utility by keeping the watermark length short and the watermarks non-conﬂicting. For the preservation of system robustness against single SP and collusion attacks, we consider publicly available genomic information like Minor Allele Frequency, Linkage Disequilibrium, Phenotype Information and Familial Information. Also, considering the fact that the attackers may know our optimality strategy in watermarking, we incorporate local diﬀerential privacy as plausible deniability factor that induces malicious inference strength. As opposed to traditional diﬀerential privacy-based data sharing schemes in which the noise is added based on summary statistic of the population data, noise is added in local setting based on local probabilities.
Open Access
Privacy-preserving computation and robust watermarking techniques for healthcare data
(2018-07) Sav, Sinem
Health and genomic data is sensitive in terms of carrying private information about individuals. One can infer inherited/genetic disorders, their occurrence probabilities, information about race, and kinship by analyzing an individual's genomic data. Furthermore, health data which is mostly collected by hospitals or other health institutions carries private information about individuals including the diseases they have at present or indicators of future diseases/disorders. While protecting such data, it is important to show that its utility is preserved and maximized since the data is used in researches. Regarding these facts, homomorphic encryption-based scheme (using Paillier cryptosystem) for the protection of health data and a novel watermarking scheme based on belief propagation algorithm for the genomic data is proposed in this work. Homomorphic encryption is used for the health data to show the ability of performing mathematical operations on the encrypted data without decrypting it with a real-life use-case. We show its practicality with the correctness and performance results. In the second part of this thesis, a watermarking scheme for genomic data is proposed to overcome the liability issues due to unauthorized sharing by service providers (SPs). Robust-watermarking techniques ensure the detection of malicious parties with a high probability and we show the probabilistic limits of this detection with di erent experimental setups and evaluation metrics. Lastly, this scheme guarantees the following with a high probability: (i) the utility is preserved, (ii) it is robust against single or colluding SP attacks, and (iii) watermark addition is compatible with the nature of the data as the proposed method considers auxiliary information that a malicious SP may use in order to remove/modify watermarked points before leaking the data.
Open Access
Watermarking based on discrete wavelet transform and q-deformed chaotic map
(Elsevier Ltd, 2017) Behnia, Sohrab; Yahyavi, Mohammad; Habibpourbisafar, Reza
Hierarchy of one-dimensional ergodic chaotic maps with Tsallis type of q-deformation are studied. We find that in the chaotic region, these maps with q-deformation are ergodic as the Birkhoff ergodic theorem predicts. q-deformed maps are defined as ratios of polynomials of degree N. Hence, by using the Stieltjes transform approach (STA), invariant measure is proposed. In addition, considering Sinai-Ruelle-Bowen (SRB) measure, Kolmogorov-Sinai (KS) entropy for q-deformed maps is calculated analytically. The new q-deformed scheme have ability to keep previous significant properties such as ergodicity, sensitivity to initial condition. By adding q-parameter to the hierarchy in order increase the randomness and one-way computation, we present a new scheme for watermarking. The introduced algorithm tries to improve the problem of failure of encryption such as small key space, encryption speed and level of security. To illustrate the effectiveness of the proposed scheme, some security analyses are presented. By considering the obtained results, it can be concluded that, this scheme have a high potential to be adopted for watermarking. It can be concluded that, the proposed novel watermarking scheme for image authentication can be applied for practical applications. © 2017 Elsevier Ltd
Open Access
Watermarking via zero assigned filter banks
(Elsevier, 2009-07-17) Yücel, Z.; Özgüler, A. B.
In order to identify the owner and distributor of digital data, a watermarking scheme in frequency domain for multimedia files is proposed. The scheme satisfies the imperceptibility and persistence requirements and it is robust against additive noise. It consists of a few stages of wavelet decomposition of several subblocks of the original signal using special zero assigned filter banks. By assigning zeros to filters on the high frequency portion of the spectrum, filter banks with frequency selective response are obtained. The information is then inserted in the wavelet-decomposed and compressed signal. Several robustness tests are performed on male voice, female voice, and music files, color and gray level images. The algorithm is tested under white Gaussian noise and against JPEG compression and it is observed to be robust even when exposed to high levels of corruption.
Open Access
Watermarking via zero assigned filter banks
(2005) Yücel, Zeynep
A watermarking scheme for audio and image files is proposed based on wavelet decomposition via zero assigned filter banks. Zero assigned filter banks are perfect reconstruction, conjugate quadrature mirror filter banks with assigned zeros in low pass and high pass filters. They correspond to a generalization of filter banks that yield Daubechies wavelets. The watermarking method consists of partitioning a given time or space signal into frames of fixed size, wavelet decomposing each frame via one of two filter banks with different assigned zeros, compressing a suitable set of coefficients in the wavelet decomposition, and reconstructing the signal from the compressed coefficients of frames. In effect, this method encodes the bit ‘0’ or ‘1’ in each frame depending on the filter bank that is used in the wavelet decomposition of that frame. The method is shown to be perceptually transparent and robust against channel noise as well as against various attacks to remove the watermark such as denoising, estimation, and compression. Moreover, the original signal is not needed for detection and the bandwidth requirement of the multiple authentication keys that are used in this method is very modest.