Discrete Particle Swarm Optimization based Data Encryption and Distribution to Mass Cloud Storage system
Keywords:
Data encryption, parallel distribution of data, Discrete Particle Swarm Optimization, cloud storageAbstract
During the last several decades, the amount of data created and the number of digital records that exist has grown exponentially due to the widespread use of data-driven applications and unified systems. The need for fast and effective data storage and retrieval is becoming more important as the data volumes handled applications continue to expand exponentially. One of the most effective ways to deal with ever-increasing data loads is to make advantage of cloud storage. Yet, maintaining data privacy while storing information outside on the cloud is a significant difficulty when using this strategy. When it comes to large data, where safeguarding data in a fast and correct way is a hard effort, data confidentiality is one of the main issues connected with cloud storage, which has contributed heavily as an impediment for cloud computing adoption throughout the globe. Our research intends to aid in the fight against cybercrime by ensuring the privacy of crucial agricultural data. We provide an architecture for protecting privacy while sharing data over the cloud, one that can scale with your data in both time and space. Combining the Particle Swarm Optimization (PSO) algorithm with parallel data dissemination and selective encryption to protect user privacy is fundamental to our architecture. Experiments and analysis of competing frameworks show that our suggested one is superior in terms of execution time and memory footprint.
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