Intelligent System for Detection of Copyright-Protected Data for Enhanced Data Security.

Abstract:

In the digital era, the proliferation of digital content has intensified concerns over intellectual property rights infringement, highlighting the need for robust copyright protection solutions. This paper presents a software solution designed to address these challenges by combining advanced algorithms with intuitive user interfaces for effective copyright enforcement. Central to the software’s functionality is the Most Significant Bit (MSB) embedding technique, which allows users to imperceptibly embed copyright or trademark information into digital images. This method modifies the MSB of pixel values to encode protection data while maintaining the visual integrity of the images. In the detection phase, the software employs Deep Convolutional Neural Networks (DCNN) to identify instances of unauthorized use or copyright infringement. By analyzing submitted images, the DCNNs use sophisticated pattern recognition algorithms to detect embedded copyright information or trademarks, promptly flagging infringements for further action. The software ensures a seamless user experience with an intuitive interface that guides users through image upload, copyright embedding, and infringement detection processes. This comprehensive approach provides a powerful tool for safeguarding intellectual property rights in the digital landscape, offering users an efficient means to protect and enforce copyright effectively.