Survey on 2D-DCT Based Image Watermarking with High Implanting Limit and Robustness

The proposed strategy displays a novel rank-based image watermarking. In watermark installing process, the host picture is separated into squares, trailed by 2-D Discrete Cosine Transform (DCT). For every picture block, a mystery key is produced utilizing RFC 2898, which incorporates techniques for making a key and introduction vector (IV) from a secret word and salt. The inserting of watermark bits is completed by adjusting the arrangement of DCT coefficients utilizing a rank-based installing rule.The created mystery key is imparted to the receiver while sending the picture.On watermark location process, with the utilization of accessible mystery key, the watermarked bits are distinguished and are extricated inview of positions of discovery lattices. The pictures transferred for general visibility is shown by DCT which assumes a vital part in keeping up the measure of the picture amid this procedure. Since the proposed watermarking strategy just uses two DCT coefficients to shroud one watermark bit, high installing limit can be accomplished. Also, this strategy is free of host signalinterference. This sought component andthe use of a blunder cushion in watermarkinserting can bring about high vigor against assaults. Hypothetical examination and trial results will exhibit the adequacy of the proposed strategy

Augmented watermarking

This thesis provides an augmented watermarking technique wherein noise is based on the watermark added to the watermarked image so that only the end user who has the key for embedding the watermark can both remove the noise and watermark to get a final clear image. The recovery for different values of noise is observed. This system may be implemented as a basic digital rights management system by defining a regime of partial rights using overlaid watermarks, together with respectively added layers of noise, in which the rights of the users define the precision with which the signals may be viewed

Improved content based watermarking for images

Due to improvements in imaging technologies and the ease with which digital content can be created and manipulated, there is need for the copyright protection of digital content. It is also essential to have techniques for authentication of the content as well as the owner. To this end, this thesis proposes a robust and transparent scheme of watermarking that exploits the human visual systems’ sensitivity to frequency, along with local image characteristics obtained from the spatial domain, improving upon the content based image watermarking scheme of Kay and Izquierdo. We implement changes in this algorithm without much distortion to the image, while making it possible to extract the watermark by use of correlation. The underlying idea is generating a visual mask based on the human visual systems’ perception of image content. This mask is used to embed a decimal sequence, while keeping its amplitude below the distortion sensitivity of the image pixel. We consider texture, luminance, corner and the edge information in the image to generate a mask that makes the addition of the watermark less perceptible to the human eye. The operation of embedding and extraction of the watermark is done in the frequency domain thereby providing robustness against common frequency-based attacks including image compression and filtering. We use decimal sequences for watermarking instead of pseudo random sequences, providing us with a greater flexibility in the choice of sequence. Weighted Peak Signal to Noise Ratio is used to evaluate the perceptual change between the original and the watermarked image

New Digital Audio Watermarking Algorithms for Copyright Protection

This thesis investigates the development of digital audio watermarking in addressing issues such as copyright protection. Over the past two decades, many digital watermarking algorithms have been developed, each with its own advantages and disadvantages. The main aim of this thesis was to develop a new watermarking algorithm within an existing Fast Fourier Transform framework. This resulted in the development of a Complex Spectrum Phase Evolution based watermarking algorithm. In this new implementation, the embedding positions were generated dynamically thereby rendering it more difficult for an attacker to remove, and watermark information was embedded by manipulation of the spectral components in the time domain thereby reducing any audible distortion. Further improvements were attained when the embedding criteria was based on bin location comparison instead of magnitude, thereby rendering it more robust against those attacks that interfere with the spectral magnitudes. However, it was discovered that this new audio watermarking algorithm has some disadvantages such as a relatively low capacity and a non-consistent robustness for different audio files. Therefore, a further aim of this thesis was to improve the algorithm from a different perspective. Improvements were investigated using an Singular Value Decomposition framework wherein a novel observation was discovered. Furthermore, a psychoacoustic model was incorporated to suppress any audible distortion. This resulted in a watermarking algorithm which achieved a higher capacity and a more consistent robustness. The overall result was that two new digital audio watermarking algorithms were developed which were complementary in their performance thereby opening more opportunities for further research

Enhancement of Media Splicing Detection: A General Framework

Digital media (i.e., image, audio) has played an influential role in today information system. The increasing of popularity in digital media has brought forth many technological advancements. The advancements, however, also gives birth to a number of forgeries and attacks against this type of information. With the availability of easy-to-use media manipulating tools available online, the authenticity of today digital media cannot be guaranteed. In this paper, a new general framework for enhancing today media splicing detection has been proposed. By combining results from two traditional approaches, the enhanced detection results show improvement in term of clarity in which anomalies are more explicitly shown, providing easier and faster way for a forensic practitioner to investigate and verify the authenticity of the target digital media. Regarding the experiment, the developed framework was tested against a number of realistic tampered (spliced) media. Moreover, the enhanced detection results are compared with traditional approaches to ensure the efficiency of our proposed method in the realistic situation

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 Ra(l) and the peak cross-correlation Rc(l). We establish the lower bound of Rc(l) and the higher bound of Ra(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

Audio watermarking techniques using singular value decomposition

In an increasingly digital world, proving ownership of files is more and more difficult. For audio files, many schemes have been put into place to attempt to protect the rights of the digital content owners. In general, these techniques fall under the classification of Digital Rights Management (DRM). Audio watermarking is one of the less invasive schemes which embeds security into the data itself instead of in an outside layer meant to encapsulate and protect the data. There are many domains in which an audio watermark can be applied. The simplest is that of the time domain; often, however, other domains may be more desirable due to greater imperceptibility and robustness to attack. Common domains include the frequency domain, or domains similar to frequency through functions such as the Wavelet Transform. One domain of particular interest is that of the Singular Value Decomposition. The goal of this thesis is to propose and test many different watermarking schemes as well as test an existing watermarking scheme operating in the SVD domain in order to assess the viability of the SVD as a watermarking carrier domain. Different carrier matrices as well as bit embedding methods are explored. The use of a standard set of audio files was used to help test the systems; a standard set of watermarking tests was unavailable, so a comparable test bed was implemented and utilized

A Property Rights Enforcement and Pricing Model for IIoT Data Marketplaces

학위논문(석사)--서울대학교 대학원 :공과대학 협동과정 기술경영·경제·정책전공,2019. 8. Jörn Altmann.The Industrial Internet of Things (IIoT) has become a valuable data source for products and services based on advanced data analytics. However, evidence suggests that industries are suffering a significant loss of value creation from insufficient IIoT data sharing. We argue that the limited utilization of the Sensing as a Service business model is caused by the economic and technological characteristics of sensor data, and the corresponding absence of applicable digital rights management models. Therefore, we propose a combined property rights enforcement and pricing model to solve the IIoT data sharing incentive problem.산업용 사물 인터넷 (IIoT) 데이터가 제품과 서비스를 위한 중요한 고급 데이터 소스로 여겨지고 있지만, 여전히 수 많은 기업들은 불충분한 산업용 사물 인터넷 데이터 공유 시스템으로 인하여 고충을 겪고 있다. 방대한 분량의 산업용 데이터가 제대로 거래되지 못하고 있으며, 이는 데이터의 커다란 가치 손실로 이어지고 있다. 본 연구에서는 서비스로서의 센싱 (Sensing as a Service) 비지니스 모델이 한정적으로 적용되고 있는 원인이 해당 정보의 경제적, 기술적 특징들을 반영하는 디지털 권리 시스템의 부재에 기인한다고 보고 있다. 따라서 본 연구에서는 산업용 사물 인터넷 데이터에 대한 지적재산권 집행 시스템과 데이터 가격산정 모델을 제안하여 산업용 사물 인터넷 데이터 공유 인센티브 문제를 해결하고자 한다.1 Introduction 1 1.1 Background 1 1.2 Problem Description 6 1.3 Research Objective and Question 8 1.4 Methodology 8 1.5 Contributions 9 1.6 Structure 10 2 Literature Review 11 2.1 Sensing as a Service 11 2.2 Economic Characteristics of IIoT Data 14 2.2.1 Property Rights of Data 18 2.2.2 Licensing of IIoT Data 23 2.3 IIoT Data Marketplaces 25 2.3.1 Use-cases and Value Propositions 30 2.3.2 Market Structures and Pricing Models 34 2.4 Digital Rights Management for IIoT 36 3 Model 44 3.1 Assumptions 45 3.2 Watermarking Technique 47 3.2.1 Function 48 3.2.2 Example 50 3.2.3 Robustness 51 3.3 Economic Reasoning 54 3.3.1 The Quality Gap 55 3.3.2 Cost of Watermarking (CoW) 57 3.3.3 Cost of Attacking (CoA) 58 4 Analytical Analysis 60 4.1 Equilibrium Between CoW and CoA 60 4.2 Determining the Optimal Quality Gap 62 4.3 Applicability of the Quality Gap Function 64 5 Conclusion 66 5.1 Summary 66 5.2 Discussion 66 6 Limitations and Future Research 68 References 70 Abstract (Korean) 79Maste