Search Results (26)

This research examines the transformation of film and TV series consumption within the contemporary media landscape, characterized by digital plenitude and Over-the-Top (OTT) dominance. The study investigates how users navigate the transition from linear broadcasting toward on-demand, platform-centric environments. Through an exploratory qualitative approach as the initial phase of a broader study, 18 semi-structured interviews were conducted with a demographically diverse group of Hungarian participants whose primary commonality is active film and TV series consumption. The findings highlight a rejection of traditional linear television, driven by an aversion to intrusive advertising and a demand for temporal autonomy. While mobile devices, particularly smartphones, are central to this shift, consumption remains predominantly stationary; users prioritize the flexibility of cross-device access within the domestic environment over mobile viewing during transit. Furthermore, the study identifies a growing friction caused by content fragmentation between different OTT platforms and rising subscription costs, while digital piracy persists as a marginal alternative. Ultimately, the study concludes that the modern audience acts as a strategic user navigating a complex ecosystem of excess. This underscores a fundamental shift where the cultural value of content is increasingly defined by the tension between individual agency and the systemic constraints of competing services. Full article

The rapid digitization of library resources has intensified the need for robust digital-rights management (DRM) mechanisms to safeguard copyright, control access, and preserve user privacy. Conventional DRM approaches are often centralized, prone to single-point-of-failure, and are limited in transparency and interoperability. To address these challenges, this article puts forward a decentralized DRM framework for library systems by leveraging blockchain technology and decentralized DRM-key mechanisms. An integrative review of the available research literature provides an analysis of current blockchain-based DRM library systems, their limitations, and associated challenges. To address these issues, a controlled experiment is set up to implement and evaluate a possible solution. In the proposed model, digital content is encrypted and stored in the Inter-Planetary File System (IPFS), while blockchain smart contracts manage the generation, distribution, and validation of DRM-keys that regulate user-access rights. This approach ensures immutability, transparency, and fine-grained access control without reliance on centralized authorities. Security is enhanced through cryptographic techniques for authentication. The model not only mitigates issues of piracy, unauthorized redistribution, and vendor lock-in, but also provides a scalable and interoperable solution for modern digital libraries. The findings demonstrate how blockchain-enabled DRM-keys can enhance trust, accountability, and efficiency through the development of secure, decentralized, and user-centric digital library systems, which will be of interest to practitioners charged with library IT technology management and to researchers in the wider field of blockchain applications in organizations. Full article

Maritime transportation requires reliable navigational safety communications to ensure vessel safety and operational efficiency. The Maritime Single Window (MSW) enables vessels to submit all maritime data digitally without human intervention. NAVTEX (Navigational Telex) messages provide navigational warnings, meteorological warnings and forecasts, piracy, and search and rescue information that require integration into automated MSW system. However, NAVTEX transmissions experience message corruption when Forward Error Correction (FEC) mechanisms fail, marking unrecoverable characters with asterisks. Current standards require discarding messages exceeding 4% error rates, resulting in safety information loss. Traditional human interpretation of corrupted messages creates limitations that prevent automated MSW integration. This paper presents the application of Masked Language Modeling (MLM) with Transformer encoders for automated NAVTEX message restoration. Our approach treats asterisk characters as masked tokens, enabling bidirectional context processing to reconstruct corrupted characters. We evaluated MLM against dictionary-matching and n-gram models using 69,658 NAVTEX messages with corruption ranging from 1% to 33%. MLM achieved 85.4% restoration rate versus 44.4–64.0% for statistical methods. MLM maintained residual error rates below the 4% threshold for initial corruption up to 25%, while statistical methods exceeded this limit at 10%. This automated restoration capability supports MSW integration while preserving critical safety information during challenging transmission conditions. Full article

Background: The issue of digital piracy is increasingly prevalent, with its proliferation further fueled by the widespread use of social media outlets such as WhatsApp, Snapchat, Instagram, Pinterest, and X. These platforms have become hotspots for the unauthorized sharing of copyrighted materials without due recognition to the original creators. Current techniques for digital watermarking are inadequate; they frequently choose less-than-ideal locations for embedding watermarks. This often results in a compromise on maintaining critical relationships within the data. Purpose: This research aims to tackle the growing problem of digital piracy, which represents a major risk to rights holders in various sectors, most notably those involved in entertainment. The goal is to devise a robust watermarking approach that effectively safeguards intellectual property rights and guarantees rightful earnings for those who create content. Approach: To address the issues at hand, this study presents an innovative technique for digital video watermarking. Utilizing the 2D-DWT along with the KAZE feature detection algorithm, which incorporates the Accelerated Segment Test with Zero Eigenvalue, scrutinize and pinpoint data points that exhibit circular symmetry. The KAZE algorithm pinpoints a quintet of stable features within the brightness aspect of video frames to act as central embedding sites. This research selects the chief embedding site by identifying the point of greatest intensity on a specific arc segment on a circle’s edge, while three other sites are chosen based on principles of circular symmetry. Following these procedures, the proposed method subjects videos to several robustness tests to simulate potential disturbances. The efficacy of the proposed approach is quantified using established objective metrics that confirm strong correlation and outstanding visual fidelity in watermarked videos. Moreover, statistical validation through t-tests corroborates the effectiveness of the watermarking strategy in maintaining integrity under various types of assaults. This fortifies the team’s confidence in its practical deployment. Full article

In this digital era, social images are the most vital information carrier on multimedia social platforms. More and more users are interested in sharing social images with mobile terminals on multimedia social platforms. Social image sharing also faces potential risks from malicious use, such as illegal sharing, piracy, and misappropriation. This paper mainly concentrates on secure social image sharing. To address how to share social images in a safe way, a social image security scheme is proposed. The technology addresses the social image security problem and the active tracing problem. First, discrete wavelet transform (DWT) is performed directly from the JPEG image. Then, the high-bit planes of the LL, LH, and HL are permuted with cellular automation (CA), bit-XOR, and singular value decomposition (SVD) computing, and their low-bit planes are chosen to embed a watermark. In the end, the encrypted and watermarked image is again permuted with cellular automation in the discrete cosine transform (DCT) domain. Experimental results and security analysis show that the social image security method not only has good performance in robustness, security, and time complexity but can also actively trace the illegal distribution of social images. The proposed social image security method can provide double-level security for multimedia social platforms. Full article

Subscription video-on-demand (SVOD) platforms face high churn rates and substantial revenue losses from SVOD content piracy, all of which limit their ability to invest in acquiring/creating content compelling enough to win and retain subscribers. Based on social exchange theory, this study argues that platforms can improve relationships with SVOD content users by offering tiered discounts in exchange for advertising/loyalty and by promoting anti-piracy messages with a prosocial (threatening) approach that emphasizes harm to filmmakers (punishment for pirates). We hypothesize that these incentives enhance subscription intention when the incentive specifications (advertising levels, loyalty levels, message approach, and message credibility) match the public’s heterogeneous dispositions (advertising attitude, loyalty attitude, justice sensitivity, and fear of punishment). In a survey on the intention to subscribe to a hypothetical new platform, we confirmed the hypothesized interactions for advertising-based discounts, loyalty-based discounts, and prosocial messages, but did not find support for threatening messages. Further exploration showed that the evaluation of platform content was much more influential than any other incentive and that tiered loyalty discounts had a remarkable capacity to enhance subscription intention. This study’s findings may help shape incentives that are more satisfying to users and ultimately more profitable for platforms. Full article

Driven by several elements, including the unwillingness to pay for material, the spread of subscription services, and the profitability of illegal activity, digital piracy has grown to be a common problem in the contemporary world. Along with financial damages for businesses and content creators, this phenomenon has legal repercussions for individuals involved in piracy and cybersecurity issues. The effective fight against digital piracy depends on an awareness of the drivers and hazards connected with this illegal activity. With an eye towards a thorough knowledge of this intricate problem, in this study, the focus centers on the reasons, attitudes, and actions behind digital piracy. Through examining how people defend their behavior in particular situations, in this study, the aim is to clarify the ethical issues and decision-making procedures related to piracy—even among otherwise law-abiding people. Combining a variety of the relevant literature and ideas, including situation ethics theory, in this study, we seek to provide insights for legislators, business players, and academics eager to meet the difficulties presented by digital piracy. This study adds to the continuous discussion on lessening the detrimental effects of digital piracy on content creators, businesses, and cybersecurity by looking at the underlying reasons for piracy and supporting legal access to material. Along with a dearth of research on the origins and moral questions of digital piracy, there is a lot of contradictory material. By examining the factors behind this unlawful activity, clarifying the complex dynamics involved, and offering understanding of the causes of digital piracy, this study seeks to close a significant void in the knowledge. The findings of this study will enable individuals to develop strategies for handling this prevalent issue in the digital era. Developing successful interventions that can reduce this illegal conduct and safeguard the interests of content producers, businesses, and cybersecurity overall depends on an awareness of the reasons behind digital piracy. This study advances the knowledge of the difficulties presented by this global phenomenon by investigating the ethical issues and decision-making procedures related to digital piracy. Full article

Marine transportation accounts for approximately 90% of the total trade managed in international logistics and plays a vital role in many companies’ supply chains. However, en-route factors like weather conditions or piracy incidents often delay scheduled arrivals at destination ports, leading to downstream inefficiencies. Due to the maritime industry’s digital transformation, smart ports and vessels generate vast amounts of data, creating an opportunity to use the latest technologies, like machine and deep learning (ML/DL), to support terminals in their operations. This study proposes a data-driven solution for accurately predicting vessel arrival times using ML/DL techniques, including Deep Neural Networks, K-Nearest Neighbors, Decision Trees, Random Forest, and Extreme Gradient Boosting. This study collects real-world AIS data in the Eastern Mediterranean Sea from a network of public and private AIS base stations. The most relevant features are selected for training and evaluating the six ML/DL models. A comprehensive comparison is also performed against the estimated arrival time provided by shipping agents, a simple calculation-based approach, and four other ML/DL models proposed recently in the literature. The evaluation has revealed that Random Forest achieves the highest performance with an MAE of 99.9 min, closely followed by XGBoost, having an MAE of 105.0 min. Full article

Digital products companies are increasingly adopting subscription pricing, but consumers who pay the subscription service may not be able to access all digital products sold on the sales platform. This paper explores the question of why some digital products are not in the subscription service of the sales platform. To address this problem, we develop an analytical model to examine two strategies of the firm. One is that the firm does not add the new product into the subscription service, the other is that the firm adds the new product into the subscription service. By comparing the profits under two sets, we find the condition under which the firm should add the new digital product into the subscription service. The results show that if the percentage of existing subscribers is below a certain threshold, and the subscription price is over a certain threshold, it is better for the firm to add the new product into the subscription service. We also analyze how the main variables affect the firm’s profit and the piracy rate. Our research provides useful insights for firms in choosing pricing schemes for the newly released product and offers advice for policymakers on controlling the piracy rate of digital products industry. Full article

Consumers are attracted by the increasing number of available SVOD platforms, but it would be too expensive to pay the subscription fees for all of them. To reduce costs, consumers can combine the use of proprietary subscriptions, non-proprietary subscriptions, and illegal streaming sites. In turn, platforms could enforce access control, a decision that might produce the desired reduction in non-proprietary subscriptions but also an undesired reduction in proprietary subscriptions. The effects of this decision and the determinants of SVOD content demand remain largely unexplored. We propose a baseline model where the SVOD content demand is driven by variety seeking, household financial situation, ethical evaluation, and social norms, as well as a change model where the subscription variation is driven by users’ trait reactance and perceived fairness of the decision. We conducted a survey on the current ways SVOD content is consumed and responses to a hypothetical access control enforcement, with four randomized versions of the authentication mode. Results confirmed many of the proposed determinants and showed a noteworthy reduction in proprietary subscriptions due to the control enforcement but no effect due to the authentication modes. All these findings may help improve future models of SVOD content consumption and better address the difficult challenge of converting unauthorized users into authorized ones. Full article

The successful investigation and prosecution of significant crimes, including child pornography, insurance fraud, movie piracy, traffic monitoring, and scientific fraud, hinge largely on the availability of solid evidence to establish the case beyond any reasonable doubt. When dealing with digital images/videos as evidence in such investigations, there is a critical need to conclusively prove the source camera/device of the questioned image. Extensive research has been conducted in the past decade to address this requirement, resulting in various methods categorized into brand, model, or individual image source camera identification techniques. This paper presents a survey of all those existing methods found in the literature. It thoroughly examines the efficacy of these existing techniques for identifying the source camera of images, utilizing both intrinsic hardware artifacts such as sensor pattern noise and lens optical distortion, and software artifacts like color filter array and auto white balancing. The investigation aims to discern the strengths and weaknesses of these techniques. The paper provides publicly available benchmark image datasets and assessment criteria used to measure the performance of those different methods, facilitating a comprehensive comparison of existing approaches. In conclusion, the paper outlines directions for future research in the field of source camera identification. Full article

The objective of this study is to improve the effectiveness of anti-piracy educational strategies by identifying unique digital pirate segments and delivering personalized campaign messages to the target audiences. In the first study, we introduced a segmentation study of digital pirates based on different types of risks involved in pirating activities. We identify four digital pirate segments (anti-pirates, hard-core pirates, performance-sensitive pirates, and finance-sensitive pirates), each demonstrating distinctive characteristics. Further profiling of the segments revealed different risk perceptions regarding gender and piracy experience. In the second study, we conduct an experiment to test the effects of targeted campaign messages for the newly identified pirating segments. Our results show that targeted piracy campaign messages have a significantly higher message persuasiveness, while they damage the attitude towards piracy. However, we found that the targeted piracy campaign messages have a marginal effect on changing the intention to pirate. Findings from this study offer useful implications for the design and implementation of anti-piracy educational campaigns. Full article

Subscription video-on-demand platforms such as Netflix and HBO Max are being increasingly challenged by the widespread practice of sharing accounts with individuals outside the household. Platforms face a massive loss of revenue due to the opportunistic behavior of many users who enjoy content without paying anything or paying only a part of the required subscription fees. This study explores which factors influence platform users to pay all, part, or none of the subscription fees. Using a cross-sectional survey from Spain, various demographic, attitudinal, and behavioral factors were identified as predictors of the patterns of full, partial, and non-payment. The findings may help platform managers tailor some interventions to monetize a larger number of actual users by deterring the opportunistic payment patterns without discouraging the full payment pattern. Full article

Recently, piracy and copyright violations of digital content have become major concerns as computer science has advanced. In order to prevent unauthorized usage of content, digital watermarking is usually employed. This work proposes a new approach to digital image watermarking that makes use of the discrete cosine transform (DCT), discrete wavelet transform (DWT), dipper-throated optimization (DTO), and stochastic fractal search (SFS) algorithms. The proposed approach involves computing the discrete wavelet transform (DWT) on the cover image to extract its sub-components, followed by the performance of a discrete cosine transform (DCT) to convert these sub-components into the frequency domain. Finding the best scale factor for watermarking is a significant challenge in most watermarking methods. The authors used an advanced optimization algorithm, which is referred to as DTOSFS, to determine the best two parameters—namely, the scaling factor and embedding coefficient—to be used while inserting a watermark into a cover image. Using the optimal values of these parameters, a watermark image can be inserted into a cover image more efficiently. The suggested approach is evaluated in comparison with the current gold standard. The normalized cross-correlation (NCC), peak-signal-to-noise ratio (PSNR), and image fidelity (IF) are used to measure the success of the proposed approach. In addition, a statistical analysis is performed to evaluate the significance and superiority of the proposed approach. The experimental results confirm the effectiveness of the proposed approach in improving upon standard watermarking methods based on the DWT and DCT. Moreover, a set of attacks is considered to study the robustness of the proposed approach, and the results confirm the expected outcomes. It is shown by the achieved results that the proposed approach can be utilized for practical digital image watermarking, and that it significantly outperforms other digital image watermarking methods. Full article

Social media has transformed the mode of communication globally by providing an extensive system for exchanging ideas, initiating business contracts, and proposing new professional ideas. However, there are many limitations to the use of social media, such as misinformation, lack of effective content moderation, digital piracy, data breaches, identity fraud, and fake news. In order to address these limitations, several studies have introduced the application of Blockchain technology in social media. Blockchains can provides transparency, traceability, tamper-proofing, confidentiality, security, information control, and supervision. This paper is a systematic literature review of papers covering the application of Blockchain technology in social media. To the best of our knowledge, this is the first systematic literature review that elucidates the combination of Blockchain and social media. Using several electronic databases, 42 related papers were reviewed. Our findings show that previous studies on the applications of Blockchain in social media are focused mainly on blocking fake news and enhancing data privacy. Research in this domain began in 2017. This review additionally discusses several challenges in applying Blockchain technologies in social media contexts, and proposes alternative ideas for future implementation and research. Full article