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Genetically Modified Ant Colony Optimization based Trust Evaluation in Cloud Computing


  • School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India


Objectives: Cloud computing is a virtualized and scalable platform which helps the users to reduce the cost incurred for setting up and maintaining an IT infrastructure. Despite the various benefits offered by cloud, it faces stringent challenges with respect to security and trust management. Trust covers the security aspects of cloud. The proposed system focuses on selection of optimal parameters used to ensure trust value. Methods: The hybridized techniques for cloud Trust Management works with a pre defined set of parameter values. Hence the trust value computed using these optimal parameters has a great impact on the overall accuracy of the trust score. We intend to use Genetically Modified Ant Colony Optimization GM-ACO technique to identify best Trust Metric Parameters (TMPs) with respect to Cloud Service Providers and it significantly outperforms compared with existing techniques. Findings: The genetically modified ACO algorithm will reduce the complexity of calculating the trust score of many service providers in the cloud environment. Applications: Managing trust in peer-to-peer systems, social network based systems, recommendation based systems, policy based systems, reputation based trust systems, trust mining systems etc.


Ant Colony Optimization, Cloud Computing, Genetic Algorithm, Trust Evaluation, Trust Management.

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