## 2 Related Work, Research Gap, and Problem Formulation
A chaotic logistic map is used for pixel shuffling. Distinct frequency domains of the image, i.e., estimate coefficient (LL) and detail confidence (LH, HL, and HH) are obtained using the Haar wavelet transform. AES encryption is applied to the lower frequency band (LL). The resulting image is scuffled by a chaotic logistic map to further improve the encryption strength. This makes malicious rebuilding very challenging. The proposed method performed well across multiple images and attained a better level of image security and a lower level of image degradation. [PERSON] et al. [16] used a hyper-chaotic system with an LDPC code. This technique implements a pseudorandom sequence generator that is constructed using a hyperchaotic system for scrambling the plaintext. This is encoded by the LDPC encoder and then encrypted by the permutation box. This helps to improve security and reliability. [PERSON] et al., in paper [17], proposed an image encryption algorithm, which uses a chaos system to generate the key and the modified AES algorithm for encryption. In a chaotic system, a small change in input makes a major change in the output. The chaos system improves the safety of image encryption algorithms. An Arnold chaos system is used to generate the key. The AES algorithm is modified by replacing proposed propagation operations with the permutable operation and replacing the linear transformation operation with the column integration operation. The advantage of this method includes reduced time complexity and increased diffusion ability of the algorithm. The keyspace analysis shows that the proposed method successfully resists brute-force attacks. The goal of the research presented in [18] by [PERSON] et al. was to secure an IoT-based smart home. The generation of a key was performed with the help of chaos and logistic maps. More randomness and computational unpredictability was added by using this method. The paper [19], presented by [PERSON] et al., focuses on securing medical images stored in the cloud. In this work, the dynamic keys are generated by the back propagation network (BPN), in which the distinctive features of an image are taken as input to the BPN. Thus, the keys generated are unique to images. The generated keys are used as an initial seed for confusion and diffusion sequence generation through a Hopfield neural network (HNN). The detailed security analysis carried out has confirmed the resiliency against the various attacks. In the paper [20], [PERSON] et al. used biometric authentication with encryption to ensure the security of images in a cloud environment. Biometric authentication is required to upload and download the file to/from the cloud. Initially, the image is compressed using discrete wavelet transform (DWT), then the hash value is calculated by SHAfollowed by the Blowfish algorithm for encryption. The encrypted file is further divided into three equal parts and its hash value is calculated. Those chunks, along with their hash values, form a hash table which is stored in the database. The proposed technique adds an extra level of security to the images stored in the cloud. The above survey observations are tabulated in Table 1 as shown below:  
From the above survey, it is concluded that:  
* Most of the approaches involve chaos-based and/or hybrid techniques for key generation and encryption. However, of the approaches are limited to academic interest rather than real-world application, because of problems such as insufficient security analysis, flawed design methodology, and low efficiency. * Few research papers focus on key generation with minimal or no key strength analysis. * None of the researchers provided a holistic end-to-end solution ensuring the security and reliability of data at rest and during transmission. To overcome these findings, we propose a comprehensive security solution comprised of the following key points:  
* The scope of our work focuses on AES, since it is widely used in the industry because of its versatility and ease of use.