# Hybrid Data Hiding Based on AMBTC Using Enhanced Hamming Code
## 1 Introduction  
Recently, the Internet space has become like a single trading world where almost all digital content is distributed because every trading system is connected by high speed Internet, such as 5G. Many people distribute digital content in this space and are constantly consuming digital content. The problem with this digital space is that a copyright protection problem occurs because digital content is easily redistributed, copied, and modified by illegal users. There are various solutions to this problem, but the commonly used method is digital watermarking [1; 2; 3], which is used to protect the integrity and reliability of digital media. Besides watermarking technology, Data Hiding (DH) technology is the most commonly used method of concealing information in digital media. The DH [4; 5; 6] technique can be used in variousfields, such as digital signatures, fingerprint recognition, authentication, and secret communication. It has been proven various times that DH could be used for secret communication, as well as the protection of the copyright of digital content. The people who use Internet communication know that the Internet is not a fully protected communication channel due to the many attackers. However, secret communication using DH can safely protect secret messages in digital cover media from the incomplete Internet channel. DH may achieve the role of a secret communication strategy only when it satisfies two important criteria. First, the quality of the cover image (including data) should not be significantly different from the quality of the original image, since the cover image must not be detected by attackers while it is transmitted. Second, it must have the ability to transmit many secret data to the receiver securely. The DH method is mainly conducted in two domains, namely the spatial domain and the frequency domain. In the spatial domain, a secret bit is concealed in the pixels of a host image directly. In the case of DH based on the spatial domain, it is applied to a grayscale image; even though the four Least Significant Bits (LSBs) [7; 8; 9; 10] of each pixel are used for information hiding, they may not be detected by the Human Visual System (HVS). Reversible DH [11; 12; 13; 14; 15; 16; 17; 18; 19; 20] is a special case of DH in the academic community. In RDH, after the embedded bits are extracted, the stego image can be recovered back to the original image without distortion. The representative RDH methods are Difference Expansion (DE) [11; 12], image compression [13], Histogram Shifting (HS) [14; 15], Prediction-Error expansion (PE) [16; 17], and encrypted images [18; 19] for privacy preserving. In the frequency domain, a cover image is converted into a frequency form, and then, the data are concealed in the coefficients of the frequency. The two most common methods based on the frequency domain are Discrete Cosine Transform (DCT) [21; 22] and Discrete Wavelet Transform (DWT) [23]. Since changing the coefficient adversely affects the image quality, it is necessary to find and change the positions of the coefficient that have a relatively small influence on the image quality during data insertion. Spatial domain methods have the merit of the ability to conceal many secret data compared to the frequency domain methods, and the quality of the image is better, while they have the demerits of compression, noise, and filtering attacks compared to the frequency domain methods. Meanwhile, excellent compression images like JPEG are preferred as digital media, because the file size is small compared to the raw images and is well transmitted. For this reason, many researchers closely studied the watermarking and DH methods based on JPEG compression a long time ago. Block Truncation Coding (BTC) [24] is one of the compression methods, and the configuration of the BTC is very simple compared to conventional JPEG. Thus, the computation time of BTC is much shorter than that of JPEG, and the quality of an image based on BTC is not significantly deteriorated compared to that of the original image.