# Implementation of MS Circle Map in Digital Image Encryption
## 1 Introduction  
Currently, communication and information technology is developing very rapidly. This development can be seen by the ease of obtaining information with the internet. The internet is a medium that can facilitate its users in obtaining various information and communication processes from any part of the world and at any time. Someone can easily send personal data to others so that the data can be widely distributed on the internet. Highly confidential personal data need to be secured from the threat of manipulation or data theft. This aims to ensure that the data are not known by unauthorized parties. Digital images are one form of digital data or information that is often targeted by crime. Cryptography is a reliable, safe, and fast security technique that can be implemented on digital images. The cryptography process is basically very simple. The original data or information is called plaintext, while the data or information that has been encoded is called ciphertext. In this case, the original image acts as plaintext. Encryption is the process of changing the original image into an encrypted image. Meanwhile, the reverse process, namely, decryption, is the process of changing the encrypted image back into the original image. The algorithm for transforming plaintext into ciphertext is called a cipher. The performance of an algorithm can be seen from the security resistance of the algorithm to attacks and its computation time. Although image encryption algorithms require a small key space and long computation time, they produce well-encrypted data. However, digital image encryption is preferred because it has a faster time and maintains security [1]. The use of chaos-based image encryption is one solution to the problem of image security. Researchers [2] developed the Logistic-Gauss Map Algorithm. The Logistic-Gauss Map Algorithm works by composing the Logistic map and Gauss map functions to produce a key space of \(1.8\times 10^{79}\) and a key sensitivity value of \(10^{-16}\). This algorithm is difficult to attack with brute force attacks. In addition, testing attacks on encrypted image data using statistical attacks and differential attacks shows that this algorithm has high durability. Recent studies have introduced new chaotic encryption techniques that further enhance security and efficiency. [PERSON] et al. [3] proposed a color image encryption scheme utilizing the KAA map combined with multiple chaotic maps, achieving a high level of security through [PERSON]'s confusion and diffusion principles. Meanwhile, [PERSON] et al. [4] developed the 2D er-map, a chaotic encryption approach based on Euler and Pi numbers, incorporating a novel diffusion technique called 'bit reversion' to manipulate pixel values. These innovations highlight the continuous evolution of chaos-based encryption, reinforcing the significance of developing more robust and efficient encryption methods such as the proposed MS Circle Map in this study. The algorithm is sequentially arranged between the logistic map and Chebyshev map [5]. This method is used to ensure the transmission of medical images. First, the image is encrypted with the logistic map. Then, the encrypted image is generated, and then, the encrypted image is encrypted again with the Chebyshev map. In other words, the medical image is encrypted in two steps using two functions. The same method is used in the decryption process. This algorithm has four parameters. When the parameter value for the logistic map is set to an impossible value, the image is no longer secure. In addition, it also takes longer to perform the encryption technique twice. The author in [6] proposed image encryption by combining the logistic map and Henon map, a process in which the image is converted into a matrix and randomized using the logistic map algorithm and continued with the XOR process for each pixel bit using the Henon map algorithm. [PERSON], [PERSON] et al.