Copyright Protection Research Articles

Liability regulation on short video platforms: balancing freedom of expression and copyright protection

Abstract The rise of short video platforms has fundamentally altered the balance between freedom of expression and copyright protection, challenging traditional legal frameworks like the Safe Harbor Principle. This paper critically examines the evolving legal landscape, with particular focus on the implications of Article 17 of the EU’s Copyright Directive in the Digital Single Market (DSM Directive), especially for small platforms, creators, and users. Through comparative analysis of international legal frameworks and case studies, the study delves into the challenges faced by stakeholders in navigating platform liability, algorithmic content moderation, and user rights. The research highlights how the existing legal environment, while aiming to protect copyright holders, often disproportionately favors large platforms, undermining the expressive freedoms and fair use rights of smaller creators and users. Furthermore, the paper addresses the role of remix culture on short video platforms, discussing how transformative works and user-generated content foster cultural diversity and innovation. It advocates for reforms that balance copyright enforcement with freedom of expression, promoting cooperative licensing models, nuanced content moderation, and expanded fair use exemptions to support a more equitable digital ecosystem where creativity, access, and protection coexist effectively.

Attack-Defending Contrastive Learning for Volumetric Medical Image Zero-Watermarking

Zero-watermarking is an emerging distortion-free copyright protection method for volumetric medical images. However, achieving both robustness against various malicious attacks and distinguishability between individual images remains challenging. In this paper, we propose a novel attack-defending contrastive learning zero-watermarking scheme (ADCL-ZW) to tackle the above challenge using deep learning-based representations. In our approach, we design an attack-defending data enrichment mechanism to enhance the watermarking robustness by generating a large number of image samples under various watermarking attacks. Subsequently, features for both watermarking distinguishability and robustness are enhanced through application of a contrastive loss. In particular, we implement a dual-stream Siamese network architecture to effectively handle both signal attacks and geometric attacks in order to enhance the wartermarking performance. Experimental results demonstrate that ADCL-ZW achieves stronger watermarking robustness and a better tradeoff between watermarking robustness and distinguishability compared with state-of-the art zero-watermarking methods. One of the highlighted metrics the false negative rate of ADCL-ZW achieves 0.01 when a fixed false positive rate is set to 1%, which is more than 13.3 times better than the benchmark methods.

Tra ined Wi thout My C onsent: Detecting Code Inclusion In Language Models Trained on Code

Code auditing ensures that the developed code adheres to standards, regulations, and copyright protection by verifying that it does not contain code from protected sources. The recent advent of Large Language Models (LLMs) as coding assistants in the software development process poses new challenges for code auditing. The dataset for training these models is mainly collected from publicly available sources. This raises the issue of intellectual property infringement as developers’ codes are already included in the dataset. Therefore, auditing code developed using LLMs is challenging, as it is difficult to reliably assert if an LLM used during development has been trained on specific copyrighted codes, given that we do not have access to the training datasets of these models. Given the non-disclosure of the training datasets, traditional approaches such as code clone detection are insufficient for asserting copyright infringement. To address this challenge, we propose a new approach, TraWiC; a model-agnostic and interpretable method based on membership inference for detecting code inclusion in an LLM’s training dataset. We extract syntactic and semantic identifiers unique to each program to train a classifier for detecting code inclusion. In our experiments, we observe that TraWiC is capable of detecting 83.87% of codes that were used to train an LLM. In comparison, the prevalent clone detection tool NiCad is only capable of detecting 47.64%. In addition to its remarkable performance, TraWiC has low resource overhead in contrast to pair-wise clone detection that is conducted during the auditing process of tools like CodeWhisperer reference tracker, across thousands of code snippets.

Editorial: Copyright protection, artistic imagery, and the adoption of responsible artificial intelligence principles

Editorial: Copyright protection, artistic imagery, and the adoption of responsible artificial intelligence principles

Protecting Street Art and Graffiti as Artistic Works Under Indian Copyright Law: An Analysis

ABSTRACT Street art, known for its temporary nature and presence in public spaces, faces challenges in copyright protection. Despite these hurdles, street art is increasingly recognized as a legitimate artistic expression warranting copyright safeguards. This abstract explores how street art can be protected under copyright law, beginning with its definition and qualification as an artistic work under copyright statutes. It addresses practical and legal issues such as authorship, ownership, and the impact of public location. This study illustrates different approaches to protecting street art through circumstances and some legal precedents. It also examines the role of moral rights and public interest in balancing artists' rights with property rights and urban aesthetics. The abstract proposes legal reforms or policy interventions to enhance copyright protection for street art while maintaining its cultural integrity, contributing to the discourse on the intersection of copyright law and urban art.

Enhancing Robustness and Imperceptibility with a Texture-Based Adaptive QIM Approach

This paper proposes a new approach for image data hiding that aims to improve both robustness and imperceptibility. The proposed approach is based on a texture-adaptive quantization index modulation (QIM) method that takes into account the local characteristics of the image texture to optimize the embedding process. The approach is evaluated using various image datasets and compared to existing state-of-the-art techniques. The results show that the proposed approach achieves better performance in terms of robustness against various image processing attacks, with BERs of zero in some attacks, while maintaining a high level of imperceptibility with PSNRs exceeding 46 decibels. It can be deduced that adaptation and normalization of the embedding strength arguments can enhance the QIM methods’ performance. The proposed approach has potential applications in image authentication, copyright protection, and data hiding.

Are We Asking Too Much of OER? A Conversation on OER from OE Global 2023

This paper examines the pervasive discourse of disruption in OER literature by recounting a facilitated conversation hosted at the 2023 Open Education Global conference held in Edmonton, Alberta. This dialogue used Bacchi’s “what is the problem represented to be” (WPR) approach to structure the conversation in four movements. The first movement problematized the concept of OER by discussing the educational challenges OER supposedly addresses, such as the high cost of textbooks. The second movement considered the genealogy, historical development, and philosophical underpinnings of OER. The third movement accounted for the disruptors within the OER movement, exploring what OER have disrupted and discussing if disruption is even a legitimate goal of OER. The fourth and final movement pivoted to examine resistors and forms of resistance to OER, including the protection of intellectual property rights, copyright concerns, and Marcuse’s idea of repressive tolerance. This single conversation generated a small but important piece of social intelligence within a much larger dialogue about open education, open pedagogy, and OER during a time of flux (characterized by intense politicization, the relentless progression of educational technology, the intensification of marketization, and the growing popularity of all-inclusive textbooks). This social intelligence can be used to guide the next transition phase for OER development. While the conversation does not offer tidy solutions or even clear recommendations, it does suggest that the next wave of OER practitioners would always do well to focus on the goals OER can achieve, not what they hope to disrupt.

PENGEMBANGAN INDUSTRI KALIGRAFI: PELUANG DAN TANTANGAN MENINGKATKAN EKONOMI UMAT ISLAM

The Islamic calligraphy industry has great potential to improve the economy of Muslims through various forms of commercialization and cultural preservation. The main opportunities include the art and collection market, education and training, as well as the development of creative industries with the application of calligraphy to design and digitalization products. Apart from that, cultural and religious tourism that utilizes calligraphy can attract tourists and improve the local economy. However, the industry faces challenges such as lack of financial support, difficulties in accessing global markets, copyright protection issues, and a lack of adequate education and training. Strategies to overcome these challenges include increased financial support, stronger copyright protection, better education and training, and the use of digital technology. With the right approach, the calligraphy industry can develop rapidly and contribute significantly to the Muslim economy.

Practical Reforms in the Field of Copyright Protection in the Republic Of Uzbekistan and Their Promising Results

This article examines the ongoing efforts to enhance legal literacy, awareness, and the protection of intellectual property rights in Uzbekistan, focusing on the “Strategy for the Development of Intellectual Property in the Republic of Uzbekistan for 2022-2026.” It highlights the significant legal reforms undertaken since the 2017-2021 development strategy, including the adoption of over a thousand laws aimed at fostering transparency, civil society engagement, and human rights protection. However, several challenges persist in the legal protection of intellectual property, such as inadequate public knowledge, weak integration of intellectual property in production processes, and insufficient coordination among relevant state bodies. The research explores how collective management of intellectual property rights, inspired by international models, can address these challenges. It also delves into the institutional reforms needed to ensure efficient legal protection, prevent counterfeit products, and promote the use of intellectual activity results in the economic and social sectors. The article concludes with recommendations for improving Uzbekistan’s intellectual property framework, increasing public engagement, and positioning intellectual property as a key driver of the country's socio-economic development.

A work of artificial generative intelligence as an object of copyright protection

A work of artificial generative intelligence as an object of copyright protection

Правовые особенности определения баз данных для их свободного использования

The article examines the normative concept of databases, as well as their differentiation from other materials. Particular attention is paid to the controversy about the attribution to big data databases, the consequences of such an action and the prospects for the development of civil legislation. The author assesses the legal definition of databases with regard to its completeness and compliance with modern legal realities. Besides, the author touches upon the importance of determining the content of databases, criteria for their free use by citizens for non-commercial purposes. It is suggested to expand the possibilities of free use of databases beyond personal purposes. An attempt is made to determine the balance between copyright protection and society's need for free use of databases, especially in the context of digitalization, when copying and use of significant amounts of data is becoming more and more accessible. The study emphasizes the importance of enabling society to use information from databases to facilitate search and access to knowledge, especially when such databases become the main sources of information in a particular field.

Blockchain for video watermarking: An enhanced copyright protection approach for video forensics based on perceptual hash function.

As a direct result of advancements in digital technology and the Internet, the copyright protection and information integrity of multimedia that are being published across the Internet have emerged as a major and urgent issue that needs to be addressed. The technique of digital watermarking may be used to protect intellectual property. In terms of authentication, resilience, storage, and capacity of digital watermarking information, there is still room for development. Blockchain's potential in video copyright protection and management applications has motivated researchers. Copyright owners and consumers may now communicate directly via copyright protection apps built on the blockchain, eliminating the need for distributers and the associated fees. Nonetheless, the current blockchain-based video watermarking solutions require storing a significant number of coordinates depending on the watermark size and are susceptible to video frame attacks on the video frame texture region. This study proposes an enhanced video copyright management approach that incorporates digital watermarking, the blockchain, and a perceptual hash function. Watermark information is stored on a blockchain structure, which also acts as a timestamp for verification purposes. To verify watermark data without the source video, a perceptual hash function is employed to compute a hash value based on the structural information of video frames. The contribution is in learning how to extract a hash function from a small number of video frames that still adequately represent a large amount of video content while also reducing the number of unnecessary video frames and the amount of computation required to summarize and index that content in a blockchain. This expedites the dissemination of copyrighted works and increases their security and readability, hence facilitating their circulation on the Internet. Our experimental results demonstrate that this approach is memory efficient, as it only needs to store one key for each key frame, regardless of the size of the watermark. Additionally, the overall robustness is greatly improved by using the blockchain's random hash function. Therefore, new and important advancements in video watermarking have been realized because of this effort.

The Solutions for The Conflict of Laws Relating to Copyright and Its Exploitation" A Comparative Study"

Determining the applicable law for copyright is a complex issue in the jurisprudence of private international law. This is because it is an intangible moral property, meaning that the nature of the subject to which the right is attributed differs from other material rights. In addition, most legislations have not established specific attribution rules for moral rights, making it difficult to determine the applicable law for copyright. Hence, the research problem is embodied in the absence of explicit and clear texts that address the issue of conflict of laws if it relates to the author’s topics moving between the scope of more than one law, which leads to an overlap in the scope of the applications of the law that related to those rights, raising the issue of which law should apply and which one is more accurate in achieving justice. The importance of this research is evident in raising the awareness among rights holders of the existence of a legal organization that protects the copyright, which may ease their minds due to their prior knowledge of the existence of a law that protects the product of their mind on the one hand and deters the aggressor on the other hand. Moreover, this study aimed to demonstrate the validity of the laws referred to by the traditional attribution rules to resolve conflicts of laws in matters related to copyright. It must be noted that the study adopted the analytical and descriptive comparative approach between Jordanian law and Iraqi law and the role of each in resolving problems arising from conflicts of laws.The study found that the Jordanian legislator specifically addressed unpublished works in Article 57 of the Copyright Protection Law, clarifying whether they fall under the law's provisions. However, we did not find an explicit provision in the Iraqi Copyright Protection Law regulating the issue of unpublished works. However, the researcher recommended that the Jordanian legislator conclude new bilateral or regional agreements in addition to joining international agreements due to the inadequacy or inappropriateness of traditional agreements related to judicial cooperation to rule on what arises from a conflict of legislative jurisdiction regarding copyright.

A Comparative Analysis of Copyright Laws Governing Music Streaming in Zambia, Kenya, and the United States

Purpose: To evaluate the adequacy of Zambia's domestic copyright law in protecting digital songs and their creators within the context of modern music streaming platforms. Methodology: A qualitative desk research approach was employed, analyzing existing Zambian copyright legislation and comparing it to relevant laws in Kenya and the United States. Findings: The study found that Zambia's copyright law is ill-equipped to protect digital songs and their creators in the digital age. The law does not explicitly address digital music streaming, leaving artists and copyright owners vulnerable to exploitation. Furthermore, the law's ambiguity regarding digital reproduction can hinder the effective enforcement of copyright rights. Unique contribution to theory, practice and policy: This study contributes to the understanding of copyright protection challenges in developing countries, particularly in the context of digital music. Its findings and recommendations offer valuable insights for policymakers and legal professionals seeking to improve copyright frameworks in Africa.

PSO-based Quaternion Fourier Transform steganography: Enhancing imperceptibility and robustness through multi-dimensional frequency embedding

This paper presents a novel steganography technique using the Quaternion Fourier Transform (QFT) in the 4D frequency domain to enhance imperceptibility and robustness in digital image embedding. Steganography, the art of hiding information within media, faces challenges in balancing security, imperceptibility, and robustness. To address this, we leverage the multi-dimensional properties of quaternions, enabling the embedding of secret data in both grayscale and color images. For grayscale images, two quaternion dimensions are utilized for intensity and secret data, while for color images, all four dimensions are employed with one reserved for metadata. The research question centers on how to maximize spatial dispersion and color similarity while maintaining high imperceptibility and robustness against attacks. Experimental results show that the proposed method improves visual imperceptibility by more than 4 % and exhibits a 13 % increase in robustness against common steganalysis attacks compared to the best state-of-the-art existing technique. These advancements highlight the potential of this method for applications in secure communication, digital watermarking, and copyright protection. By combining the quaternion mathematical framework with a novel optimization strategy, this approach significantly improves upon traditional steganography methods.

Secure and Robust Dual Watermarking for Western Blot Images

The rapid growth of digital data sharing has created a pressing need to safeguard the integrity, authenticity, and security of bioanalytical images, such as Western blots, online. To address this challenge, we propose a novel hybrid biometric watermarking technique that combines randomised singular value decomposition (RSVD), discrete wavelet transform (DWT), schur transform, pseudo magic cube, and chaotic encryption, making the watermarking of Western blot images more secure, robust, and imperceptible. Our approach surpasses state-of-the-art methods, ensuring imperceptible watermarking and robust protection against tampering and unauthorised use. By integrating spatial and transform-domain techniques, we achieve superior performance, outperforming existing methods with a peak signal-to-noise ratio (PSNR) of 48.7581, structural similarity index (SSIM) of 0.9998, a normalised correlation (NC) of 0.9996, an average number of changing pixel rate (NPCR) of 0.9961, and an average unified average changing intensity (UACI) of 0.3334. Our technique sets a new standard for digital image protection in scientific research, addressing critical challenges in tampering, copyright protection, and data security. With its high performance and security, our approach enables the trustworthy sharing and publication of Western blot images in the digital era.

Quantum color image watermarking scheme based on quantum discrete cosine transform

Quantum watermarking is a technique that embeds specific information into a quantum carrier, used for digital copyright protection. This paper introduces a new quantum color image watermarking method that combines Quantum LOG (QLOG) edge detection with Quantum Discrete Cosine Transform (QDCT) technology. First, edge detection is used on the RGB channels of the quantum color image. This helps identify the best channel for embedding the watermark. Next, the image is decomposed using the quantum Haar wavelet transform (QHWT). The image is then processed with QDCT, selecting the mid-frequency parts for watermark embedding. Using QDCT improves the watermark’s resistance to JPEG compression. The invisibility of the watermark is verified by assessing its Peak Signal-to-Noise Ratio (PSNR) and histogram. Comparative analysis shows strong resistance to various noise attacks. Simulation results confirm that the watermarking technique maintains high visual quality and resists different adversarial attacks.

Generative network copyright protection method based on iris information watermarking

Generative network copyright protection method based on iris information watermarking

Problems of copyright protection for gaming content

The article is devoted to a comprehensive study of the current issues of copyright protection of game content in the context of the rapid development of the video game industry. The study examines the peculiarities of legal protection of various elements of video games, including software code, audiovisual components, storylines and characters. It analyses the main challenges faced by developers and publishers in protecting their intellectual property rights, including unauthorised copying, piracy and unlicensed modifications. The author analyses the terminology of the industry, in particular, the concept of ‘video game’ which is widely used in international practice. At the same time, the author establishes that the term ‘computer game’ prevails in the European legal space. This terminological difference reflects regional peculiarities in approaches to classification and legal regulation of interactive entertainment products. Despite certain semantic differences, both terms cover electronic games operating on various digital platforms. With the development of online capabilities, video games have moved far beyond the isolated and closed subculture they once were. Video games now create an interactive virtual community and a thriving business that is part artistic expression, part sporting competition and part mass entertainment. A comprehensive analysis of a wide range of court precedents from different jurisdictions relating to the protection of rights to video content in the field of interactive entertainment was carried out. The study of these court decisions allowed the author to identify the key legal approaches and principles applied in cases of copyright infringement of video game elements. It is found that the differences between video games and other intellectual property objects have led to difficulties in determining the legal regime most appropriate to their specifics. Video games include a variety of constituent elements, many of which are eligible for legal protection. The growing involvement of video games in civilian circulation has given rise to the urgent problem of copyright protection for game content.

FaceDefend: Copyright Protection to Prevent Face Embezzle

With the rapid evolution of deep learning and the advent of artificial intelligence, the metaverse has emerged as a significant technology. Within the metaverse, diverse elements such as rich applications and realistic digital avatars provide users with immersive experiences, but it poses a series of security problems. Current research predominantly focuses on the data storage and transmission processes from the perspective of blockchain and the Internet of Things to achieve the protection of the metaverse. However, there exists a gap in security research on the digital avatar generation process. Given that digital avatars are the primary entities engaging in social activities within the metaverse and are crafted based on real face images, the virtual character can be generated easily by stealing the user’s face image and controlled to interact with others. In order to deal with the above problems, we propose a novel method to prevent the misuse of faces, which maintains the security of the metaverse by protecting facial data and thus preventing its misuse. We explore the common architecture of generative models and propose a defense method based on copyright protection to prevent face embezzling. Firstly, we utilize the copyright protection module to obtain copyright protection information. Secondly, we utilized the defense control module to ensure the representation of the protected images occurs errors in the latent space of the generation model. Therefore the subsequent generation task output fails, which effectively protects the face data and prevents the generation of digital avatars. Furthermore, the results on public datasets and across multiple generative models present unnatural outputs, indicating the excellence of our defense and transfer capabilities.