Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Rajalakshmi, S.
- An Quality Based Enhancement of User Data Protection via Fuzzy Rule Based Systems in Cloud Environment
Abstract Views :179 |
PDF Views:2
Authors
Affiliations
1 Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, IN
1 Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, IN
Source
ICTACT Journal on Soft Computing, Vol 6, No 3 (2016), Pagination: 1177-1182Abstract
So far, in cloud computing distinct customer is accessed and consumed enormous amount of services through web, offered by cloud service provider (CSP). However cloud is providing one of the services is, security-as-a-service to its clients, still people are terrified to use the service from cloud vendor. Number of solutions, security components and measurements are coming with the new scope for the cloud security issue, but 79.2% security outcome only obtained from the different scientists, researchers and other cloud based academy community. To overcome the problem of cloud security the proposed model that is, "Quality based Enhancing the user data protection via fuzzy rule based systems in cloud environment", will helps to the cloud clients by the way of accessing the cloud resources through remote monitoring management (RMMM) and what are all the services are currently requesting and consuming by the cloud users that can be well analyzed with Managed service provider (MSP) rather than a traditional CSP. Normally, people are trying to secure their own private data by applying some key management and cryptographic based computations again it will direct to the security problem. In order to provide good quality of security target result by making use of fuzzy rule based systems (Constraint & Conclusion segments) in cloud environment. By using this technique, users may obtain an efficient security outcome through the cloud simulation tool of Apache cloud stack simulator.Keywords
Cloud Service Provider, Cloud Vendor, RMMM, Fuzzy Rule Systems, Managed Service Provider, Cloud Clients, Cloud Security, Apache Cloud Stack Simulator Tool.- Preventive Signature Model for Secure Cloud Deployment through Fuzzy Data Array Computation
Abstract Views :162 |
PDF Views:3
Authors
Affiliations
1 Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, IN
1 Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, IN
Source
ICTACT Journal on Soft Computing, Vol 7, No 2 (2017), Pagination: 1402-1407Abstract
Cloud computing is a resource pool which offers boundless services by the form of resources to its end users whoever heavily depends on cloud service providers. Cloud is providing the service access across the geographic locations in an efficient way. However it is offering numerous services, client end system is not having adequate methods, security policies and other protocols for using the cloud customer secret level transactions and other privacy related information. So, this proposed model brings the solution for securing the cloud user confidential data, Application deployment and also identifying the genuineness of the user by applying the scheme which is referred as fuzzy data array computation. Fuzzy data array computation provides an effective system is called signature retrieval and evaluation system through which customer's data can be safeguarded along with their application. This signature system can be implemented on the cloud environment using the cloud sim 3.0 simulator tools. It facilitates the security operation over the data centre and cloud vendor locations in an effective manner.Keywords
Cloud Vendor, Fuzzy Data Array, Cloud Server, Data Centre, Cloud Service Provider, Cloudsim, Signature Evaluator.References
- Tram Truong-Huu and Chen-Khong Tham, “A Novel Model for Competition and Cooperation among Cloud Providers”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, pp. 251-265, 2014.
- Alain Tchana, et al., “A Self-Scalable and Auto Regulated request Injection Benchmarking Tool for Automatic Saturation Detection”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, pp. 279-291, 2014.
- Luis Tomas and Johan Tordsson, “An Automatic Approach to Risk-Aware Data Center Overbooking”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, pp. 292-305, 2014.
- Yang Wang and Wei Shi, “Budget-Driven Scheduling Algorithms for batches of Map Reduce Jobs in Heterogeneous Clouds”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, pp. 306-319, 2014.
- Bei Guan, Yanjun Wu, Liping Ding and Yongji Wang, “CIV Scheduled Communication-Aware Inter-VM Scheduling Technique for Decreased Network Latency between Co-Located VM’s”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, 2014
- Shanjiang Tang, Bu-Sung Lee and Bingsheng He; “Dynamic MR: A Dynamic Slot Allocation Optimization Framework for Map Reduce Clusters”, IEEE Transactions on Cloud Computing, Vol. 2, No. 3, pp. 333-347, 2014.
- B. Poornima and T. Rajendran, “Improving Cloud Security by Enhanced Hasbe using Hybrid Encryption Scheme”, Proceedings of World Congress on Computing and Communication Technologies, pp. 312-314, 2014.
- Chang Liu, Jinjun Chen, Laurence T. Yang, Xuyun Zhang, Chi Yang, Rajiv Ranjan and Ramamohanarao Kotagiri, “Authorized Public Auditing of Dynamic Big Data Storage on Cloud with Efficient Verifiable Fine-Grained Updates Parallel and Distributed Systems”, IEEE Transactions on Parallel and Distributed Systems, Vol. 25, No. 9, pp. 2234-2244, 2014.