Watermarking Channel Research Articles

Evaluation of WATERMARK Channel for Underwater Communication using Dual Tree Complex Wavelet Transform based Orthogonal Frequency Division Multiplexing Model

Underwater communication is one of the important research areas which involves design and development of communication systems that can demonstrate high data rate and low Bit Error Rate (BER). In this work three different modulation schemes are compared for their performances in terms of BER and Peak to Average Power Ratio (PAPR). The realistic channel model called WATERMARK is used as a benchmark to evaluate channel performances. The mathematical model is developed in MATLAB and channel environments such as Norway Oslo fjord (NOF1), Norway Continental Shelf (NCS1), Brest Commercial Harbour (BCH1), Kauai (KAU1, KAU2) are considered for modelling different underwater channels. The data symbols are modulated using Dual Tree Complex Wavelet Transform (DTCWT) Orthogonal Frequency Division Multiplexing (OFDM) model to generate multi subcarriers and are demodulated at the receiver considering underwater channel environments. The BER results are evaluated for channel depth less than 10m and 10-50m. An improvement of 2x10-2 in terms of BER is observed when compared with Fast Fourier Transform (FFT) based OFDM model.

Soft Symbol Decoding in Sweep-Spread-Carrier Underwater Acoustic Communications: A Novel Variational Bayesian Algorithm and Its Analysis

Sweep spread carrier (S2C) based underwater acoustic (UWA) communications is a practically attractive but less explored modulation scheme in the published literature. In this paper, we present a rigorous treatment of the S2C communication receiver design and propose a data detection scheme that can handle challenging UWA channels. State-of-the-art S2C receivers based on the gradient heterodyne processing are only effective when the path delay and Doppler spread are moderate. We develop a new variational soft symbol decoding (VSSD) algorithm based on the principle of variational Bayes’ inference for a general linear channel model. In channels with moderate delay and Doppler spreads, we show that the VSSD algorithm is equivalent to the existing gradient heterodyne receivers for S2C communications. We apply the VSSD algorithm to the i.i.d. Gaussian multiple-input multiple-output channel and show, through numerical simulations, that it far outperforms the minimum mean squared error (MMSE) data detection. We illustrate the dramatic improvement in the performance of the VSSD based S2C receiver in two different models of simulated UWA channels and two contrasting measured UWA environments publicly available in the Watermark channel dataset. The proposed VSSD algorithm recovers data symbols at a signal-to-noise ratio (SNR) which is at least 10 dB (8 dB) lower than the MMSE decoder for uncoded (rate 2/3 LDPC coded) communications over UWA channels where the existing receivers either fail completely or must compromise on the data rate to maintain the bit error rate (BER) performance.

Over-Complete-Dictionary-Based Improved Spread Spectrum Watermarking Security

This letter presents a theoretical analysis of the security of two over-complete-dictionary-based improved spread spectrum (ISS) watermarking systems, i.e., subspace-ISS (sub-ISS) and random matching pursuit (RMP)-ISS, in comparison with the conventional orthogonal-transform-based ISS system. Considering Kerckhoffs’ principle and the watermarked-only attack (WOA) scenario, we derive the associated decoding regions under brute force attack in which the adversary randomly draws probing keys until getting access to the watermarking channel. We first reveal that the sub-ISS system is as equally secure as the conventional ISS system in terms of message decoding, but the sensed key could provide computational security of the spreading key. More importantly, the RMP-ISS system is shown to be securer than the conventional ISS system for it being able to survive brute force attack. Based on the findings, we further propose an empirical design mechanism that optimizes the security of the RMP-ISS scheme.

Convolutionally Coded Hopping Pattern for MFSK Modulation in Underwater Acoustic Communication

A convolutionally coded $M$ -ary frequency shift keying (MFSK) modulation scheme for underwater acoustic communication is introduced. It uses a rate $1/\log _{2}{M}$ inner convolutional code, whose coded symbols are used as transmission symbols. An interleaver in the frequency domain is applied to improve the average channel clearing time. It thereby achieves almost the same data rate as a comparable uncoded frequency hopped frequency shift keying (FH-FSK) modulation scheme, but obtains the error correcting properties of the convolutional code. Bit and packet error rates are evaluated on the additive white Gaussian noise (AWGN) channel and the so-called Watermark channel model, which is a benchmark for underwater acoustic modulation schemes based on sea trial measurements. The JANUS standard which uses convolutionally coded FH-FSK is used for comparison. On the AWGN channel, the proposed scheme achieves a gain of 4 dB with respect to the required $E_{b}/N_{0}$ for a given packet error rate (PER) compared with JANUS. In the Watermark scenarios, the best proposed-scheme achieves a PER $10^{-3}$ at more than 10 dB lower $E_{b}/N_{0}$ than the JANUS implementation.

Watermark BER and Channel Capacity Analysis for QPSK-Based RF Watermarking by Constellation Dithering in AWGN Channel

Radio frequency (RF) watermarking is the technology that embeds the hidden information in the normal communication signals without extra bandwidth, which could be used to identify authentication or transmit secret information. Constellation dithering (CD) is one of the RF watermarking schemes and usually used for quadrature phase shift keying signals. In this letter, the two available CD watermarking schemes are analyzed by unified theoretical model and then a new CD scheme is proposed based on the model. All the three schemes are investigated to provide the bit-error-rate formulas for the carrier symbols and watermark bits, and the watermark channel capacities have been presented for the three schemes. The numerical analysis shows that the proposed scheme has the largest watermark channel capacity in the same inaudibility constraint.

Anti-counterfeiting digital watermarking algorithm for printed QR barcode

Anti-counterfeiting watermarking technology provides a potential way to prevent quick response (QR) barcode from being copied or forged, and many relevant algorithms for digital QR barcode appeared recently. However, as for printed QR barcode, there is no actual research achievement published. This paper studies anti-counterfeiting techniques for printed QR barcode. The primary performance parameter, decoding rate of QR barcode as well as detection rate of digital watermark, is defined and discussed. A multi-channel robust watermarking scheme based on discrete wavelet transform (DWT) is proposed. In the watermarking scheme, the DWT domain is divided into non-overlapping rectangular areas as called watermarking channels. Channel watermark as well as anti-counterfeiting watermark is embedded into each watermarking channel. At the stage of anti-counterfeiting watermark extracting, the distortion rates of the watermarking channels are estimated by channel watermark. Based on the distortion rates, anti-counterfeiting watermark is computed by a well-designed linear estimation algorithm, whose validity is theoretically proved by analyzing anti-counterfeiting watermark bit error. The experimental results show that the detection rate of anti-counterfeiting watermark is greatly improved with the proposed scheme, and that we can correctly extract anti-counterfeiting watermark from printed QR image by choosing reasonable parameters.

A New Watermarking Scheme Based on Antipodal Binary Dirty Paper Coding

We investigate the performance of a watermarking system in which the encoder is forced to use a binning strategy based on antipodal binary-valued sequences. The use of antipodal binary random binning has several advantages, including the possibility of relying on simple and effective binary code constructions and the ease with which this kind of schemes can cope with amplitude scaling. By relying on a novel binning strategy, we derive a lower bound of the Gelfand-Pinsker capacity of the watermark channel when the encoder is forced to use an antipodal binary auxiliary random variable, showing that for low to moderate bit-rates, the bound coincides with Costa's capacity. We exploit the properties of the new binning strategy, to develop a practical watermarking system and show that the new scheme outperforms previous constructions, exhibiting very good performance also in the presence of gain attack. Preliminary results on audio signals show that the new scheme retains its good performance also when used for the watermarking of real multimedia data.

The theoretical limits of watermark spread spectrum sequence.

At present, the spread spectrum (SS) sequences used in watermark include i.i.d. random sequences and the sequences used in SS communications. They appear earlier than digital watermark. Almost no researchers pay attention to whether they are really fit for watermark. In this paper, we compare the SS watermark channel and the traditional SS communication channel. We find out that their correlation property is different. Considering cropping and translation attacks, we define watermark auto- and cross-correlation and propose Loose Autocorrelation and Tight Cross-Correlation (LAC&TCC) properties for SS watermark. The LAC&TCC properties are that, whether or not synchronized, the autocorrelation is equal or close to 1 and the cross-correlation is equal or close to 0. Accordingly, the peak correlation is divided into the peak autocorrelation R a(l) and the peak cross-correlation R c(l). We establish the lower bound of R c(l) and the higher bound of R a(l), respectively. The two bounds indicate that, no matter how small the cover is reserved, the extractor can always find a threshold to distinguish auto- and cross-correlation in theory.

A New QIM-Based Watermarking Method Robust to Gain Attack

We propose a new watermarking method based on quantization index modulation. A concept of initial data loss is introduced in order to increase capacity of the watermarking channel under high intensity additive white Gaussian noise. According to the concept some samples in predefined positions are ignored even though this produces errors in the initial stage of watermark embedding. The proposed method also exploits a new form of distribution of quantized samples where samples that interpret “0” and “1” have differently shaped probability density functions. Compared to well-known watermarking schemes, this provides an increase of capacity under noise attack and introduces a distinctive feature. Two criteria are proposed that express the feature numerically. The criteria are utilized by a procedure for estimation of a gain factor after possible gain attack. Several state-of-the-art quantization-based watermarking methods were used for comparison on a set of natural grayscale images. The superiority of the proposed method has been confirmed for different types of popular attacks.

A New Measure of Watermarking Security: The Effective Key Length

Whereas the embedding distortion, the payload, and the robustness of digital watermarking schemes are well understood, the notion of security is still not completely well defined. The approach proposed in the last five years is too theoretical and solely considers the embedding process, which is half of the watermarking scheme. This paper proposes a new measure of watermarking security, called the effective key length, which captures the difficulty for the adversary to get access to the watermarking channel. This new methodology is applied here to additive spread spectrum schemes where theoretical and practical computations of the effective key length are proposed. Experimental protocols using either Monte Carlo simulations, region approximation, or rare event probability estimator allow good evaluation of this quantity. For improved spread spectrum (ISS), our analysis exhibits setups where 1) the robustness and the security of the scheme are superior to spread spectrum and 2) estimating the secret keys from the observations only is not the best way to break the scheme. Moreover, a comparison with correlation aware spread spectrum (CASS) shows that ISS offers a better security than CASS for a given robustness.

Error correcting codes for robust color wavelet watermarking

Abstract This article details the conception, design, development and analysis of invisible, blind and robust color image watermarking algorithms based on the wavelet transform. Using error correcting codes, the watermarking algorithms are designed to be robust against intentional or unintentional attacks such as JPEG compression, additive white Gaussian noise, low pass filter and color attacks (hue, saturation and brightness modifications). Considering the watermarking channel characterized by these attacks, repetition, Hamming, Bose Chaudhuri Hocquenghem and Reed-Solomon codes are used in order to improve the robustness using different modes and appropriate decoding algorithms. The article compares the efficiency of different type of codes against different type of attacks. To the best of our knowledge this is the first time that the effect of error-correcting codes against different attacks are detailed in a watermarking context in such a precise way: describing and comparing the effect of different classes of codes against different type of attacks. This article clearly shows that list decoding of Reed-Solomon codes using the algorithm of Sudan exhibits good performance against hue and saturation attacks. The use of error correcting codes in a concatenation mode allows the non-binary block codes to show good performance against JPEG compression, noise and brightness attacks.

Information theory applications in error bit rate analysis of digital image watermarking

An error bit rate (EBR) analysis of digital image watermarking is proposed based on information theory. The relationship between watermarking capacity and EBR is also discussed. Two watermarking communication models are established for the EBR analysis of digital image watermarking. In the watermarking communication models, channel coding is introduced to transmit digital watermark in the watermarking channel. Another concept, watermark payload capacity, is introduced. EBR of watermarking will keep a lower lever if its payload capacity is less than the channel capacity.

Channel equalization using watermark as a training sequence

Abstract. In this paper blind equalization algorithms based on digital watermarking are presented. Training sequence is sent along with the data in the form of watermark. Robust CDMA based watermarking algorithm is used to watermark the data. Watermark, which is spread over the data, does not consume extra bandwidth. So with the help of extracted watermark channel can be equalized just by using simple mean square algorithm. Two algorithms for equalization are proposed in this paper. In algorithm I the receiver does not require to know training sequence in advance. Using algorithm II, the sender does not require to send training sequence either, and data can still be equalized using simple LMS algorithm at low computational complexity.

High Watermarking Capacity Based on Spatial Domain Technique

Watermarking capacity refers to the amount of information we are able to insert into the image. Low signal to noise ratio is a phenomenon of watermarking channels, which severely limits the capacity. The aim of this study is to develop a digital watermarking model, which can find out the possibility to embed maximum amount of data in an image without degrading the quality of watermarked image. In this approach, the host image will be partitioned into non-overlapping blocks and passing an imaginary plane in the three critical pixels. The characteristics of this plan should not be changed after embedding message; then the same characteristics will be used to evaluate the embedded capacity in the extracting module.

Improving Robustness of Quantization-Based Image Watermarking via Adaptive Receiver

In this paper, the watermarking channel is modeled as a generalized channel with fading and nonzero mean additive noise. In order to improve the watermark robustness against the generalized channel, we present an optimized watermark extraction scheme by using an adaptive receiver for quantization-based watermarking. In the proposed extraction scheme, we adaptively estimate the decision zone of the binary data bits and the quantization step size. A training sequence is embedded into the original image together with the informative watermark. The estimation of the decision zone takes advantage of the response function of the training sequence. Compared to those watermarking schemes without receiver adaptation, the main improvement is the enhanced robustness against median filtering, image intensity Direct Current (DC) change, histogram equalization, color reduction, image intensity linear scaling, image intensity nonlinear scaling such as Gamma correction etc.

The edge process model and its application to information-hiding capacity analysis

In this paper, the problem of capacity analysis of data-hiding techniques in a game information-theoretic framework is considered. Capacity is determined by the stochastic model of the host image, by the distortion constraints, and by the side information about the watermarking channel state available at the encoder and at the decoder. The importance of the proper modeling of image statistics is emphasized, and for this purpose, a novel stochastic nonstationary image model is proposed that is based on geometrical priors, the so-called edge process model. Being mathematically simple and tractable, the edge process model outperforms the estimation-quantization (EQ) and spike process models in reference applications such as denoising. Finally, this model allows us to obtain a realistic estimate of maximal embedding rates, and in particular, it is shown that the expected capacity limit of real images is significantly lower than previously reported.

Audio watermarking under desynchronization and additive noise attacks

Digital watermarking is often modeled as the transmission of a message over a noisy channel denoted as "watermark channel". Distortions introduced by the watermark channel result mainly from attacks and may include interference from the original signal. One of the main differences with classical transmission situations stems from the fact that perceived distortions have to be taken into account. However, measuring the perceived impact an attack has on a watermarked signal is currently an unsolved problem. Possible means of circumventing this problem would be 1) to define the distortion in a so-called "perceived domain" and define an "ad hoc" equivalence between objective and perceived distortion or 2) to define an "equivalent distortion" by removing from the attack noise the part that is correlated to the host signal. This paper concentrates on the second approach and first shows that the resulting "equivalent" attack is a particular case of a thoroughly studied channel: filtering plus additive noise. However, the approach in this paper emphasizes the fact that the additive noise in the model has to be decorrelated with the signal. Then, the formalism is applied to (desynchronization plus noise) attacks on audio signals. In this context, this paper provides the corresponding capacities, as well as optimal "attack" and "defense" strategies in a game theory context.

Improving the Payload of Watermarking Channels via LDPC Coding

The payload increase of watermarking channels via the use of low-density parity check (LDPC) codes is considered. The bit error rate and payload size problem is addressed in the light of the performance of typical transform-domain spread-spectrum watermarking techniques. Simulation results indicate that the information payload can be doubled via judicious use of LDPC codes vis-a/spl grave/-vis the performance of the Bose-Chaudhuri-Hochquenghem and repetition codes.

Robust optimum detection of transform domain multiplicative watermarks

Digital watermarking is an emerging technique to protect data security and intellectual property right. Identification or verification of watermarking patterns can be achieved by detecting watermarks in received signals. However, one of the biggest challenges in watermarking detection is that the strengths of the watermark signals will change after being distorted by an attacker in a watermarking channel. Meanwhile, the embedding strengths may be adapted to the original signals, which are unknown at the receiver end. Further, the original signals are often highly non-Gaussian. Although some work has been done on optimum detection of watermarks, the uncertainty of watermark signal strengths and real statistical behavior of multimedia contents have not been taken into account simultaneously. Much more study is needed to enhance the performance of watermarking systems. Since multiplicative watermarks are robust and well suited for copyright protection, this paper presents our investigation on robust optimum detection of multiplicative watermarks. For sub-band transformed domains such as the discrete cosine transform (DCT), discrete wavelet transform (DWT), and pyramid transform, a class of generalized correlators is constructed based on the generalized Gaussian distributions. Thresholding methods to achieve a given false alarm rate, and the performance analyses are provided. The square-root detector is designed and demonstrated to have near performance for a large set of natural images and can be employed as a universally optimal detector or decoder for images and video. The locally most powerful detection method is then extended to DFT domain multiplicative watermarking, with the magnitudes of coefficients modeled by the Weibull distributions. Another class of detectors is built based on this statistical modeling. The robust optimum detection of multiplicative watermarks can be applied to copyright notification, enforcement, and broadcast monitoring. We have applied the robust optimum watermarking detection to combined audio and video watermarking.

Analyses of error correction strategies for typical communication channels in watermarking

Most watermarking techniques rely on redundancy where signature bits are encoded in a sufficiently large amount of sites for robustness against distortions and attacks while the watermark energy is kept low enough to remain imperceptible. The goal of this paper is to explore some strategies for exploiting this redundancy using error correcting codes. In some watermarking techniques bits are extracted via hard-decisions leading to a binary symmetric channel model while in others the extraction is carried out with soft-decisions leading to a additive Gaussian channel model. First, we consider error correcting codes for very high error rates of the watermarking channel where the trade-offs of Bose–Chaudury–Hocquenheim (BCH) and repetition codes are investigated. We also present the performance and a fast implementation of soft-decoders. We give two potential realizations of soft-decoding, namely, Viterbi decoder for convolutional codes and a new algorithm for soft-BCH decoding.