A Dual Model Watermarking Framework for Copyright Protection in Image Processing Networks

Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely usedin model copyright protection, but there are two challenges: (1) designinguniversal trigger sample watermarking for different network models is stilla challenge;(2) existing methods of copyright protection based on trigger swatermarking are difficult to resist forgery attacks. In this work, we propose adual model watermarking framework for copyright protection in image processingnetworks. The trigger sample watermark is embedded in the trainingprocess of the model, which can effectively verify the model copyright. And wedesign a common method for generating trigger sample watermarks based ongenerative adversarial networks, adaptively generating trigger sample watermarksaccording to different models. The spatial watermark is embedded intothe model output. When an attacker steals model copyright using a forgedtrigger sample watermark, which can be correctly extracted to distinguishbetween the piratical and the protected model. The experiments show that theproposed framework has good performance in different image segmentationnetworks of UNET, UNET++, and FCN (fully convolutional network), andeffectively resists forgery attacks.

Novel copyright protection scheme for digital content

A novel copyright protection scheme for digital content is presented, which is a private watermarking scheme based on the watermark embedding in the DCT domain and watermark extraction Using independent component analysis （ICA）. The system includes the key for watermark extraction and the host image. The algorithm splits the original image into blocks and classifies these blocks based on visual masking, that is, noise visibility function （NVF）. Watermark components with different strength are inserted into chosen direct current components of DCT coefficients according to the classifier. The watermark extraction is based on the characteristic of the statistic independence of the host image, watermark and key. Principle component analysis （PCA） whitening process and FastICA techniques are introduced to ensure a blind watermark extraction without requiring the original image. Experirnental results show the proposed technique is robust under attacks such as image filtering and adding noise, cropping and resizing. In addition, the proposed private watermarking system can be improved to the application of the DTV content protection system.

Transparent System for Digital Media Copyright Protection in Mobile Business

At present, in mobile business, the secure environment in the terminal of users has not been embedded, many cryptology-based methods can not be directly used to protect the copyright of digital media. Under this situation, a transparent system based on watermark for digital right management and digital copyright protection is proposed in this paper. The transparent system is called WDRM （watermark-based digital rights management） and transparent to users. Its core is WDRM Agent. In this paper, system inner model and procession are designed in detail at first, including the registration, the downloading, the super distribution, and the cooperation. Because the watermark embedding and the extraction algorithms are the kernel in this architecture, we also discuss how to choose and design the algorithms. Then we establish a package for all algorithms in WDRM Agent.

Research on Copyright Protection Method of Material Genome Engineering Data Based on Zero-Watermarking

In order to effectively solve the problem of copyright protection of materials genome engineering data,this paper proposes a method for copyright protection of materials genome engineering data based on zero-watermarking technology.First,the important attribute values are selected from the materials genome engineering database;then,use the method of remainder to group the selected attribute values and extract eigenvalues;then,the eigenvalues sequence is obtained by the majority election method;finally,XOR the sequence with the actual copyright information to obtain the watermarking information and store it in the third-party authentication center.When a copyright dispute requires copyright authentication for the database to be detected.First,the zero-watermarking construction algorithm is used to obtain an eigenvalues sequence;then,this sequence is XORed with the watermarking information stored in the third-party authentication center to obtain copyright information to-be-detected.Finally,the ownership is determined by calculating the similarity between copyright information to-be-detected and copyright information that has practical significance.The experimental result shows that the zero-watermarking method proposed in this paper can effectively resist various common attacks,and can well achieve the copyright protection of material genome engineering database.

Semi-Fragile Watermarking for Copyright Protection and Image Authentication

In this paper, we propose a semi-fragile wattr-marking technology forcopyright protection and image authentication We transform the image into wavelet domain and groupthe four adjacent wavelet coefficients Utilizing the characteristics of the humanvisual system, weembed a digital signal into the average of the four adjacent wavelet coefficients since the mean hasbetter stability than single wavelet coefficient. This method neednt original image when extractsthe watermark. Experimental results show the effectiveness of this method which is robust to commonimage process and fragile to malicious attack.

A TTP-Independent Watermarking Protocol Based on Commutative Cryptosystem for Copyright Protection in E-Commerce

For the purpose of deterring unauthorized duplication and distribution of multimedia contents in e-commerce, some Buyer-seller watermarking protocols which combine of traditional watermarking and fingerprinting techniques have been proposed, However, previous protocols have potential risk from trust third party （TTP） because all entities （including multi-buyers and multi-sellers） mentioned in protocol construct a star tupology like connection, in which the watermark certification authority （WCA） serves as the central point in the interaction and therefore its availability probably turns out to be the vital bottleneck of reliability and efficiency to the whole system. Secondly, WCA holds entire information about watermark used hy Buyers so that an innocent Buyer can he found as guilty if WCA collude with the Seller. In this paper, we propose a watermarking protocol to address the problems using cryptographic technologies in phase of watermark generation. The resuh is a TTP-independent and collusion-secure buyer-seller watermarking protocol.

A Image Copyright Protection Method Using Zero-Watermark by Blockchain and IPFS

Behind the popularity of multimedia technology,the dispute over image copyright is getting worse.In the digital watermark prevention technology for copyright infringement,watermark technology is considered to be an important technology to overcome data protection problems and verify the relationship between data ownership.Among the many digital watermarking technologies,zero watermarking technology has been favored in recent years.However,the existing zero watermark technology in the implementation process often needs a trusted third party to store watermarks,which may make the data too central,data storage security is low and copyright registration costs are too high,which creates a rare problem.The decentivization and information cannot be tampered of blockchain technology’s nature find new methods for image copyright protection.This paper studies the role of zero watermark algorithm in the image copyright and its complete storage and certification scheme,proposes a zero watermark image protection framework based on blockchain,and builds a system according to the framework.Combined with blockchain and zero watermarking technology,the framework uses inter IPFS(Inter Planetary File System)to solve the problem of blockchain efficient storage and sharing of large files.In addition,the application of user copyright information,image image query and image trading in the system are realized based on smart contracts,which solves the problem of lack of trusted third parties.Experiments show that the scheme is feasible and robust to various attacks.

Research on Software Design of Image Copyright Protection in the Field of Education

Nowadays, image copyright protection is one of the key points of information security in the field of education. Based on the transient property of human vision, the anti-theft and copyright protection strategies are proposed based on the idea of animation synthesis. In this paper, experiments are designed and compared from multiple perspectives. The results show that the strategy based on animation synthesis can not only ensure the browsing effect of images, but also effectively achieve the purpose of preventing interception via screenshot and protecting the legitimate rights of the original images.

Weakly Supervised Object Localization with Background Suppression Erasing for Art Authentication and Copyright Protection

The problem of art forgery and infringement is becoming increasingly prominent,since diverse self-media contents with all kinds of art pieces are released on the Internet every day.For art paintings,object detection and localization provide an efficient and ef-fective means of art authentication and copyright protection.However,the acquisition of a precise detector requires large amounts of ex-pensive pixel-level annotations.To alleviate this,we propose a novel weakly supervised object localization(WSOL)with background su-perposition erasing(BSE),which recognizes objects with inexpensive image-level labels.First,integrated adversarial erasing(IAE)for vanilla convolutional neural network(CNN)dropouts the most discriminative region by leveraging high-level semantic information.Second,a background suppression module(BSM)limits the activation area of the IAE to the object region through a self-guidance mechanism.Finally,in the inference phase,we utilize the refined importance map(RIM)of middle features to obtain class-agnostic loc-alization results.Extensive experiments are conducted on paintings,CUB-200-2011 and ILSVRC to validate the effectiveness of our BSE.

Few-Shot Graph Classification with Structural-Enhanced Contrastive Learning for Graph Data Copyright Protection

Open-source licenses can promote the development of machine learning by allowing others to access,modify,and redistribute the training dataset.However,not all open-source licenses may be appropriate for data sharing,as some may not provide adequate protections for sensitive or personal information such as social network data.Additionally,some data may be subject to legal or regulatory restrictions that limit its sharing,regardless of the licensing model used.Hence,obtaining large amounts of labeled data can be difficult,time-consuming,or expensive in many real-world scenarios.Few-shot graph classification,as one application of meta-learning in supervised graph learning,aims to classify unseen graph types by only using a small amount of labeled data.However,the current graph neural network methods lack full usage of graph structures on molecular graphs and social network datasets.Since structural features are known to correlate with molecular properties in chemistry,structure information tends to be ignored with sufficient property information provided.Nevertheless,the common binary classification task of chemical compounds is unsuitable in the few-shot setting requiring novel labels.Hence,this paper focuses on the graph classification tasks of a social network,whose complex topology has an uncertain relationship with its nodes'attributes.With two multi-class graph datasets with large node-attribute dimensions constructed to facilitate the research,we propose a novel learning framework that integrates both meta-learning and contrastive learning to enhance the utilization of graph topological information.Extensive experiments demonstrate the competitive performance of our framework respective to other state-of-the-art methods.

MBE:A Music Copyright Depository Framework Incorporating Blockchain and Edge Computing

Audio copyright is a crucial issue in the music industry,as it protects the rights and interests of creators and distributors.This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on“blockchain+edge computing mode,”abbreviated as MBE,by integrating edge computing into the Hyperledger Fabric system.MBE framework compresses and splits the audio into small chunks,performs Fast Fourier Transform(FFT)to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information.After being confirmed by various nodes on the Fabric alliance chain,audio fingerprint information and copyright owner information are recorded on the chain and broadcast to all participants.Blockchain technology’s characteristics of being tamper-proof and traceable not only reform the trust mechanism of copyright protection but also endow edge computing with the ability to resist tampering and single-point attack,greatly enhancing the robustness of the music copyright certification system.Meanwhile,edge computing mode improves Fabric blockchain’s processing speed and transaction throughput.Experimental results show that MBE’s performance is better than traditional systems regarding efficiency,storage demand and security.Compared to the traditional Fabric system without edge computing mode,MBE exhibits a 53%higher deposition efficiency and a 48%lower storage space requirement.

New Fragile Watermarking Technique to Identify Inserted Video Objects Using H.264 and Color Features

The transmission of video content over a network raises various issues relating to copyright authenticity,ethics,legality,and privacy.The protection of copyrighted video content is a significant issue in the video industry,and it is essential to find effective solutions to prevent tampering and modification of digital video content during its transmission through digital media.However,there are stillmany unresolved challenges.This paper aims to address those challenges by proposing a new technique for detectingmoving objects in digital videos,which can help prove the credibility of video content by detecting any fake objects inserted by hackers.The proposed technique involves using two methods,the H.264 and the extraction color features methods,to embed and extract watermarks in video frames.The study tested the performance of the system against various attacks and found it to be robust.The evaluation was done using different metrics such as Peak-Signal-to-Noise Ratio(PSNR),Mean Squared Error(MSE),Structural Similarity Index Measure(SSIM),Bit Correction Ratio(BCR),and Normalized Correlation.The accuracy of identifying moving objects was high,ranging from 96.3%to 98.7%.The system was also able to embed a fragile watermark with a success rate of over 93.65%and had an average capacity of hiding of 78.67.The reconstructed video frames had high quality with a PSNR of at least 65.45 dB and SSIMof over 0.97,making them imperceptible to the human eye.The system also had an acceptable average time difference(T=1.227/s)compared with other state-of-the-art methods.

A New Mechanism Based on Similar Clouds Watermark for Database’s Information Security

This paper studies the digit watermark technology of numeric attributes in relational database for database's information security. It proposes a new mechanism based on similar clouds watermark and gives the concept of similar clouds. The algorithm SCWA that can insert the meaning watermark and detect it from the watermarked data is described. The mechanism can effectively and broadly scatter the watermark in the database; therefore the watermark is very robust. Key words copyright protection - digit watermark - similar clouds - clouds model CLC number TP 311. 52 Foundation item: Supported by the National Natural Science Foundation of China (60273072) and 863 Hi-technique Research (2002AA4Z3450)Biography: HUANG Min(1979-), female, Ph. D candidate, research direction: database's information security

Research of Anti-Plagiarism Monitoring System Model

We proposed a flexible anti-plagiarism system model based on user-defined plagiarism standards. We also proposed PlagLazy and format-legacy phenomena that plagiarist will remain format-legacy such as soft-enter symbol in his DOC document after plagiarizing material from web and corresponding optimized algorithm which improves the speed of comparison. Our model is suitable for the anti-plagiarism and monitoring of large document collections, and it can also be used in digital library, E-learning and other fields.

Chaos-Based Multipurpose Image Watermarking Algorithm

To achieve the goal of image content authentication and copyright protection simultaneously, this paper presents a novel image dual watermarking method based on chaotic map. Firstly, the host image was split into many nonoverlapping small blocks, and the block-wise discrete cosine transform （DCT） is computed. Secondly, the robust watermarks, shuffled by the chaotic sequences, are embedded in the DC coefficients of blocks to achieve the goal of copyright protection. The semi-fragile watermarks, generated by chaotic map, are embedded in the AC coefficients of blocks to obtain the aim of image authentication. Both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.

A Weighted Algorithm for Watermarking Relational Databases

A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.

A Novel Database Watermarking Technique Using Blockchain as Trusted Third Party

With widespread use of relational database in various real-life applications,maintaining integrity and providing copyright protection is gaining keen interest of the researchers.For this purpose,watermarking has been used for quite a long time.Watermarking requires the role of trusted third party and a mechanism to extract digital signatures(watermark)to prove the ownership of the data under dispute.This is often inefficient as lots of processing is required.Moreover,certain malicious attacks,like additive attacks,can give rise to a situation when more than one parties can claim the ownership of the same data by inserting and detecting their own set of watermarks from the same data.To solve this problem,we propose to use blockchain technology—as trusted third party—along with watermarking for providing a means of rights protection of relational databases.Using blockchain for writing the copyright information alongside watermarking helps to secure the watermark as changing the blockchain is very difficult.This way,we combined the resilience of our watermarking scheme and the strength of blockchain technology—for protecting the digital rights information from alteration—to design and implement a robust scheme for digital right protection of relational databases.Moreover,we also discuss how the proposed scheme can also be used for version control.The proposed technique works with nonnumeric features of relational database and does not target only selected tuple or portion(subset)from the database for watermark embedding unlike most of the existing techniques;as a result,the chances of subset selection containing no watermark decrease automatically.The proposed technique employs zerowatermarking approach and hence no intentional error(watermark)is added to the original dataset.The results of the experiments proved the effectiveness of the proposed scheme.

DWT-Based Robust Color Image Watermarking Scheme

A scheme of embedding an encrypted watermark into the green component of a color image is proposed. The embedding process is implemented in the discrete wavelet transformation （DWT） domain, The original binary watermark image is firstly encrypted through scrambling technique, and then spread with two orthogonal pseudo-random sequences whose mean values are equal to zero, and finally embedded into the DWT low frequency sub-band of green components, The coefficients whose energies are larger than the others are selected to hide watermark, and the hidden watermark strength is determined by the energy ratio between the selected coefficients energies and the mean energy of the subband. The experiment results demonstrate that the proposed watermarking scheme is very robust against the attacks such as additive noise, low-pass filtering, scaling, cropping image, row （or column ） deleting, and }PEG compression.

New scheme of dynamic traitor tracing against the immediate rebroadcast attack

Traitor tracing schemes are introduced to combat the piracy scenarios. The notation of dynamic traitor tracing is proposed by Fiat and Tassa, which fights against rebroadcast of decrypted content. In this paper, using the idea of searching user address level by level, a new dynamic traitor tracing scheme based on a multilevel structure of user set is constructed. The scheme proposed can efficiently combat with the immediate rebroadcast attack, and possesses lower tracing complexity. Importantly, the tracing scheme can be applicable to systems with different sizes of subscriber sets.