Secure data storage and retrieval system using hybridization of orthogonal knowledge swarm optimization and oblique cryptography algorithm in cloud

Distributed computing provides extensive storage capacity for customers to carry out their applications with no investment in infrastructure. As a result, many companies do their trade in the Public Space. For an instance to process the initial information set, many mediator information sets will be used for information exhaustive applications. However, protecting the protection of the intermediate information set is a difficult job. To solve this problem, numerous algorithms are implemented in the literature for retrieval problems. As a result, in my previous study, the optimal privacy protection of cloud-based data search was proposed using an oppositional cuckoo search and an ElGamal encryption algorithm. However, the downside is ElGamal, and the ciphertext is twice as long as the plain text. In addition, this algorithm is slower and necessary for randomness. To overcome the problem in this work, we propose the Optimum oblique Cryptography (OOCC) Algorithm for Encryption. In this, we primarily choose the equivalent node starting with and create the transitional dataset and apply the Opposition Cuckoo Search (OCS) algorithm. We choose confidential material from the intermediate information. We then encrypt sensitive data using the OECC algorithm. We now use an algorithm for orthogonal wisdom element optimization (OLPSO) for input generation. The information can be stored securely in the cloud after encoding; we recover the query dependent statistics securely from the cloud; performance of proposed effort on a variety of procedures, such as data transfer rate, encryption time, memory usage, and information thrashing.