Successful cloud computing (CC) lets businesses and people outsource data processing, storage, and access. CC has numerous advantages but new privacy and security risks. Data owners lose control over their data at external providers, making it subject to misuse, distribution, and access. The current data security method involves encryption. Encryption increases computing complexity, especially when data is dispersed throughout several CSP servers. Simple secrecy technologies include encryption and fragmentation. HSSOA-FEW is a hybrid sparrow search optimisation method for cloud security employing fragmentation and encryption. HSSOA-FEW holds data on CSP server with minimal encryption. HSSOA-FEW considers security and data storage. HSSOA-FEW also included sparrow search algorithm (SSA) with particle swarm optimisation. Additionally, HSSOA-FEW uses fused encryption and decryption. HSSOA-FEW controls and secures cloud servers. The suggested HSSOA-FEW system is tested extensively to improve performance. The experiments indicated HSSOA-FEW outperformed others.
TopIntroduction
Cloud computing (CC) provides cloud users with a flexible resource that could be acquired and released on demand (Xie et al., 2021). Cloud users pay for the leased resource on a pay-as-you-go basis. Such pay-as-you-go strategy elastic and resource provisioning attracts research institutes or enterprises for running their workflow application on cloud at lower cost without the need of maintaining and purchasing any framework (Zhou et al., 2021). In CC, IT resource is frequently encapsulated as virtual machines (VMs). The running VM is named VM instances. Usually, cloud user wants to achieve the computational outcome of the workflow within a provided deadline at low implementation cost (Fattahi & Hasanipanah, 2021). In general, the more computational power a VM has, the high its price. To balance the runtime of a workflow and execution cost, task scheduling of a workflow onto VM instance is highly crucial for CC. But the flexible management of cloud resources and the complicated workflow structure makes them more challenging (Siddiqui & Raza, 2021). In CC platform, customers of cloud services don’t need anything means not going into details about the execution and they access the data and complete the computing task with an Internet connection (Murlidhar et al., 2020). Throughout the access to the data and computing, the users don’t know the location of the data or where the information is put away. Therefore, here the security issue stands up quickly. Data security in the CC is challenging when compared to the conventional data system (Rodríguez-Mazahua et al., 2021). Figure 1 defines the general overview of fragmentation process.
Figure 1. General overview of fragmentation process
Two natural protection approaches were developed for satisfying confidentiality requirements fragmentation and encryption (Bhatawdekar et al., 2021). Encryption contains in encrypting the information beforehand outsourcing them to external provider for making them intelligible to the users who hold the decryption keys and protect them from unauthorized eyes (involving the provider itself). Even though symmetric and asymmetric encryption schemes are adopted for performance reason, most proposal assumes the adoption of symmetric encryption (Bahache, 2018). Encryption can be imposed at distinct levels of granularity: column, table, individual cell, and tuple. Encrypting at the level of table indicates that the entire relationship should be returned to the user for access, which requires substantial transmission and leaves the entire query processing work to the user (Zeng et al., 2021). Fragmentation comprises splitting the attribute of relation R producing dissimilar vertical views (fragments) so the sensitive relation is characterized by a relation constraint c once the attribute in c doesn’t appear in the fragments, and same (openly accessible) fragment could not be combined via nonauthorized user. It should be noted that singleton constraint is enforced properly only if the corresponding attribute doesn’t appear in any fragment (Singh & Choudhary, 2021). However, Fragmentation could be considered the case of potential relation amongst attributes (that can enable linking or present inferences).
This paper presents a hybrid sparrow search optimization algorithm based on fragmentation with encryption (HSSOA-FEW) technique for cloud security. The presented HSSOA-FEW technique effectually saves the data on CSP server with minimal quantity of encryption. The presented HSSOA-FEW technique considered the security and data storage aspects. In addition, the HSSOA-FEW system was mainly dependent upon the hybridization of sparrow search algorithm (SSA) with particle swarm optimization (PSO) algorithm. Moreover, the HSSOA-FEW technique employs a fused approach for encryption and decryption processes. The presented HSSOA-FEW technique can manage the cloud server and accomplishes security. To ensure the improved performance of the presented HSSOA-FEW system, an extensive range of experiments are executed.