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DRDS-CSSO: Division and Replication of Data Security via the Crossover based Swallow Swarm Optimization in Cloud


Ashish Sharma and Aasheesh Shukla
Abstract

In cloud computing, data is outsourced to a third party. This outsourcing may lead to security issues. Nodes within the cloud and other users may produce an attack which leads to the compromise of data. So, cloud requires a high security measures. The data retrieval time should optimized by the scheme employed for security purpose. The compromise authentication should be increased and breaking effort needed for compromising a single node should be decreased by an employed optimization techniques. In order to have a secured cloud, this work proposes a Division and Replication of Data security via the Crossover based Swallow Swarm Optimization (DRDS-CSSO) method. The data is divided to form fragments and they are distributed to the nodes in the cloud by this method. Only a single fragment of data is stored in one node. This is done to ensure that, meaningful data is not revealed if that node is successfully attacked by an attacker. In cloud computing, security issues are dealt with Crossover Swallow Swarm Optimization (CSSO) method. Acceleration coefficients are computed accurately by a new inertia weight. This is computed by combining various weights calculated by crossover operation. This overall computation results in enhanced security level. In order to enhance the security, file fragments are replicated in a controlled way. Genetic Replication Algorithm (GRA) and Division and Replication of Data Performance security (DROPS) are used to compare the performance of proposed DRDS-CSSO scheme.

Volume 11 | 11-Special Issue

Pages: 237-243

DOI: 10.5373/JARDCS/V11SP11/20192953