Artificial Intelligence for Detecting Media Piracy

Stolikj, Milosh; Jarnikov, Dmitri; Wajs, Andrew

doi:10.5594/jmi.2018.2827181

Cited by 4 publications

(15 citation statements)

References 11 publications

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“…On the other hand, in the active identification of infringing sites, twenty-one [25,[28][29][30][31][32][33][34][35][64][65][66][67][68][69][70][71][72][73][74][75] significant research contributions were compiled. Among these, three [65][66][67] engage in non-technical actions such as manual search and reporting, contributing to the legal takedown of offending sites.…”

Section: Taxonomy For the Protection And Detection Of Infringing Mult...mentioning

confidence: 99%

“…Six projects [28,29,[68][69][70][71] follow a technical route, involving surveillance and cyber patrolling within the IoE. Regrettably, only twelve initiatives [28][29][30][31][32][33][34][35][72][73][74][75] implement one or more AI/ML techniques for identifying infringing content on the IoE, and of these, only eight [28][29][30][31][32][33][34][35] are considered closely related studies. Notably, a single article [25] stands out for its purely technical approach to the defensive and active aspects.…”

Section: Taxonomy For the Protection And Detection Of Infringing Mult...mentioning

confidence: 99%

“…The present study addresses the previously posed research questions, focusing on two fundamental axes: firstly, the design of a detailed taxonomy in the domains of SafeGuarding and Active, aimed at managing infringing sites in the IoE, and secondly, the proposal of an innovative methodology for identifying websites that host multimedia content with potential copyright infringement. This research delves into a field that, so far, has received limited attention in the scientific literature [28][29][30][31][32][33][34][35]. The main contributions of this work are as follows:…”

Section: Introductionmentioning

confidence: 99%

“…-Technical [28,29,[68][69][70][71] involves any technical procedure that allows for traversing the IoE to identify websites, links, URLs, P2P platforms, File Transfer Protocol (FTP) endpoints, torrents, and storage clouds where an identified infringing multimedia resource is residing. -AI/ML-driven [28][29][30][31][32][33][34][35][72][73][74][75] includes advanced schemes that harness the power of AI/ML algorithms to efficiently perform cyber patrolling by traversing the IoE using NLP techniques, Supervised Learning (SL), Non-Supervised Learning (NSL), and DL analyses to analyze, discover, and present potential infringing multimedia content.…”

mentioning

confidence: 99%

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Methodological Approach for Identifying Websites with Infringing Content via Text Transformers and Dense Neural Networks

Hernandez-Suarez,

Sanchez-Perez,

Toscano-Medina

et al. 2023

Future Internet

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The rapid evolution of the Internet of Everything (IoE) has significantly enhanced global connectivity and multimedia content sharing, simultaneously escalating the unauthorized distribution of multimedia content, posing risks to intellectual property rights. In 2022 alone, about 130 billion accesses to potentially non-compliant websites were recorded, underscoring the challenges for industries reliant on copyright-protected assets. Amidst prevailing uncertainties and the need for technical and AI-integrated solutions, this study introduces two pivotal contributions. First, it establishes a novel taxonomy aimed at safeguarding and identifying IoE-based content infringements. Second, it proposes an innovative architecture combining IoE components with automated sensors to compile a dataset reflective of potential copyright breaches. This dataset is analyzed using a Bidirectional Encoder Representations from Transformers-based advanced Natural Language Processing (NLP) algorithm, further fine-tuned by a dense neural network (DNN), achieving a remarkable 98.71% accuracy in pinpointing websites that violate copyright.

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Section: Taxonomy For the Protection And Detection Of Infringing Mult...mentioning

confidence: 99%

Section: Taxonomy For the Protection And Detection Of Infringing Mult...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Methodological Approach for Identifying Websites with Infringing Content via Text Transformers and Dense Neural Networks

Hernandez-Suarez,

Sanchez-Perez,

Toscano-Medina

et al. 2023

Future Internet

View full text Add to dashboard Cite

show abstract

“…By combining more creative elements and algorithmic models, AIGC technology will be able to generate more unique and interesting video content. With the continuous progress of natural language processing, computer vision, and other technologies, the intelligence of AIGC technology in video generation and editing will be further improved [13][14].…”

Section: Introductionmentioning

confidence: 99%

Principles of AIGC technology and its application in new media micro-video creation

2024

Applied Mathematics and Nonlinear Sciences

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AIGC, as a new generation of intelligent generation technology, provides new ideas for the progress and development of the new media field. This study constructs a communication model for new media micro-video creation based on the information communication model, analyzing the communication and development of new media micro-video creation. Combining the application characteristics of AIGC technology in new media micro-video creation and the needs of new media micro-video creation, it proposes the information hiding improvement method based on the GAN model and diffusion model. It constructs the AIGC optimization system based on new media micro-video creation. The model’s application effect in new media micro-video creation is explored after it passes the performance test. The results show that the average scores of all the indicators of the sense of using experience are above 3.5, the overall average score of micro-video creation is 4.12, and the peak traffic and cumulative traffic of the works created by utilizing this method have been improved by 17,000 and 1,910,000, respectively. The efficiency and quality of micro-video creation can be enhanced by using this study as a feasible reference.

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