# A Survey of Intellectual Property Rights Protection in Big Data Applications +
## 4 Technical Solutions for Protecting Intellectual Property Rights
### Watermarking Algorithms  
The process of embedding data into a multimedia element, such as a picture, audio, or video file, is known as watermarking. For security reasons, this encoded data may later be retrieved from or discovered in the multimedia. The embedding algorithm, extraction algorithm, and detection method make up a watermarking algorithm.  
Based on the scores of watermarking and non-watermarking algorithms, there are several approaches, such as precision, recognition, peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), normalized cross-correlation (NC), correlation coefficient (CC), and bit error rate (BER). PSNR, SSIM, and NC are used to estimate the differences between the original image and the result after noise reduction or deformable image. One of the applications of PSNR, SSIM, and NC is to calculate the similarity measure between the original image and the watermarked image to understand the robustness of the watermarking method to the invisibility of the watermark, and the unit is dB. To evaluate the robustness of watermarking in audio applications, SNR [52] and ODG [53] are used. SNR is a standard evaluation by measuring perceived transparency based on a statistical standard introduced by IFPI to measure the similarity rate between main and watermarked signals. ODG is a standard parameter measured by the EAQUAL [53] open source software.  
Watermarks can be incorporated into a transform domain or a pixel domain. Embedded watermarks in multimedia applications should be undetectable, reliable, and big.  
Most recent works [54; 55; 56; 57; 58; 59] applied copyright of multimedia data to the problem of color image watermarking. Table 3 summarizes the important overview of copyright applications for multimedia data based on state-of-the-art techniques. [PERSON]. [54] proposed a color image watermarking algorithm that has high performance and can be applied in various watermarking schemes based on discrete cosine transform (DCT) and discrete Hartley transform (DHT). Unfortunately, the effectiveness of this method is low when the loss of pixel values occurs after a zoom-out attack. Schur decomposition was first proposed by [55] where it was applied to color image watermarks. The idea of this method is to develop an algorithm for color image watermarking that has high robustness, large watermarking capacity, and high security. However, the effectiveness of this method is low when the image is attacked with salt-and-pepper noise. The multi-watermarking technology for color images was presented by [56]. His method finds the optimal embedding region solutions with several different embedding methods when applied to a color multi-watermark using adaptive multiple embedding factors (AMEF), particle swarm optimization and gray wolf optimizer (PSO-GWO), discrete wavelet transform (DWT), and singular value decomposition (SVD). The weakness of this method is that the total size of all watermarks should be smaller than the size of the selected regions in the image, making the method unreliable for larger watermarks. One of the recent works, ref. [57] focused on simple geometric attacks, such as cropping, shifting, rotating and distorting, which give good results compared to the state-of-the-art methods using fusion domain color watermarking based on Haar transformation and image correction. However, the size of the input image and the watermark image must still be the same. To integrate the color domain into the RGB channel, the quaternion QR decomposition (QQRD) proposed by [58] is used to find an effective way to apply the watermark. However, the resilience of the proposed method is limited by Gaussian noise and scaling correction up to 50%.  
In the application of audio watermarking, ref. [59] used the fuzzy inference system, singular value decomposition (SVD), and discrete cosine transform (DCT) to create a compromise method for robustness, transparency, and capacity. The results show that the proposed method has a great advantage over other state-of-the-art methods.