A Survey on Evolving Optimal Encryption Methods in Cloud Computing Data Forensics

Characteristics of cloud computing, such as adaptability and openness, call into question several long-held beliefs about data forensics and access control. Companies use the cloud for its many advantages, including its vast resources in terms of storage, network, and processing power. Concerns about data security remain a major barrier to the widespread use of the cloud. Therefore, in most data forensics applications, plays an essential role. Multiple cryptographic approaches have been proposed and put into practice to ensure the privacy and integrity of transmitted data. Optimization issues emerge often in engineering domains, including structural design, scheduling, economic dispatch, and portfolio investment. The optimization strategies they employ are inspired by nature. Cuckoo Search (CS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO) are only a few of the algorithms developed in recent years. CS is a recently developed meta-heuristic algorithmic rule that has demonstrated indisputable practical performance on a variety of continuous optimization problems. Like the exploration done on optimization in cloud computing, this survey article covers the biggest challenges that many strategies confront. This method helps academics provide better answers to issues with optimizing encryption techniques.