# A Novel Fragmented Approach for Securing Medical Health Records in Multimodal Medical Images
## 2 Recent Studies
Their method has the objective of keeping the difference among the discrete cosine transform (DCT) coefficient at the same position in neighboring blocks as much as possible. Their method was proven effective and robust. In ref. [13], the authors proposed a steganography method using a new operation adversarial embedding (ADV-EMB) for embedding secret messages in the cover image and proving robustness against Convolutional Neural Network (CNN) steganalysis. In ref. [14], the authors proposed a method for creating a stego image without altering the cover image. Instead, they proposed using partially identical sets of secret images as stego images, which can be obtained from a natural image dataset. Essentially, they have a dataset of natural images, and when they want to embed a secret message, they search the dataset for images that contain partial duplicates of the secret image while the receiving end uses the patches to recover the secret message. This approach can approximately recover secret messages but is still resistant to steganalysis tools. In ref. [15], the authors proposed a method to embed the secret message in quantized DCT coefficients of the JPEG file through the addition of the independent realizations of the heteroscedastic noise to pixels to make the stego image resemble the cover image. In ref. [16], the authors proposed a channel-dependent payload partition strategy using amplification of channel modification probabilities, thus embedding adaptive capacity. The modification probabilities of the RGB channels are increased all at once, and thereby, embedding could be clustered. This method achieved better performance against color image steganalysis techniques. In ref. [17], the authors proposed a secure image steganography framework using the stego key-directed adaptive LSB (SKA-LSB) substitution technique as well as multilevel cryptography. Two-level encryption is used to encrypt the stego key, while the secret message is encrypted using multilevel encryption. Adaptive LSB is then used to embed the encrypted message in the cover image. The method was proven to be effective in maintaining visual image quality and security. In ref. [18], the authors proposed a bit-flipping technique for hiding secret data in a cover image. Blocks are divided into two pixels, and thus, they flip one or two LSBs of the pixel in order to conceal information. The method achieved good results in PSNR, Quality Index (Q.I), and hiding capacity. In ref. [19], the authors investigated three quantum color image steganography techniques based on LSB. The first method uses only one channel to conceal data. The second is based on the LSB XORing Method, and the last uses two channels to conceal data. MATLAB is used to analyze the schemes. Acceptable performance was achieved by analyzing the metrics such as PSNR and Histogram graphs. In ref. [20], the authors proposed a steganography method that is a combination of both edge detection and XOR coding, which is used to hide data in the Integer Wavelet Transform (IWT) or spatial domain of the cover image. Better imperceptibility and security against the texture feature steganalysis method were achieved. In ref. [21], the authors proposed a technique that is a combination of steganography, cryptography, and watermarking, which they dubbed as Next Gen. The patient's information was encrypted initially, and then steganography and watermarking techniques were used for authenticity using LSB methods. The results were a good tradeoff between payload, security, and visual characteristics. In ref. [22], the authors proposed a steganography method to increase the payload. Their method relies on the similarity between pixels. Different metrics, including MSE and PSNR, were used for testing. They were able to hide 10,000 characters in 256 \(\times\) 256 images without using compression techniques. In ref. [23], the authors enhanced medical record security by proposing the use of 3 DES and LSB. Java programming was used as the tool, and results showed good security and reliability. In ref.