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Poorvadevi, R.
- A Security Aware User Access Privileges in Cloud through Fuzzy Reasoning Approach
Abstract Views :252 |
PDF Views:1
Authors
Affiliations
1 Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, Tamil Nadu, IN
1 Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, Tamil Nadu, IN
Source
International Journal of Distributed and Cloud Computing, Vol 2, No 2 (2014), Pagination: 32-36Abstract
So far, the web browsers act as a major cloud client, used to access the computational resources from the public cloud with online connectivity. In these cases, there is a possibility of security issues related to the resources which are shared through online, untrusted public channel service access, in secured protocol usages on cloud services. So to eliminate these problems, a new on-demand security service needs to be introduced in the cloud computing environment. Cloud computing is a forum which offers massive amount of resources to its end users. As cloud providers offer tremendous services to the stakeholders, still there is a security lacking in cloud. Even though cloud is offering securityas-a-service, still customers are afraid to use that service which is offered by the cloud service provider itself, because they are maintaining and storing lots of confidential information on cloud database. Number of security solutions and measurements are coming with the new scope to prevent the customer owning data in cloud. Still, we are getting the security solution up to 79% only. So, this proposed model will be a suitable approach for cloud users to safeguard their data. Using this, we can obtain the efficient security outcomes by getting the distinguished kind of input values from the users and justifying identity of users by setting access parameter values to prove the authenticity through the fuzzy reasoning technique.Keywords
Cloud Vendor, Fuzzy Reasoning, Cloud Service Provider, Input Recognizer, Hytrust Data Control.
- Strengthening the Process of User Legitimacy in Cloud Environment Using Fuzzification Approach
Abstract Views :179 |
PDF Views:2
Authors
Affiliations
1 CSE Department, SCSVMV University, Kanchipuram, Tamil Nadu, IN
2 SCSVMV University, Enathur, Kanchipuram, Tamil Nadu, IN
1 CSE Department, SCSVMV University, Kanchipuram, Tamil Nadu, IN
2 SCSVMV University, Enathur, Kanchipuram, Tamil Nadu, IN
Source
International Journal of Knowledge Based Computer System, Vol 4, No 1 (2016), Pagination: 25-29Abstract
In cloud computing lots of resources are consumed by the distinct end users whoever are strongly connected with the web. CSP is providing enormous amount of services to its requested clients. However service provider is offering plenty of services, still there is a lack in security and privacy factors at the client end. Whatever transaction and operations are performed by the cloud users those are safely maintained on the cloud database. Once the resources/services are transferred from CSP to the customer's location at that instance, hackers get the loophole from the customers based on the way they use the service. So, securing the user data is the essential task in the cloud service access platform. So, this proposed work is mainly used to authenticate cloud users and also protect the client data from the attackers as well as restricting the attacker's entry in the cloud environment. This can be achieved by using the fuzzy computational process, that is called fuzzification process to find the security solution which is optimal to the user focal point. The targeted result can be processed on the cloud apache stack tools.Keywords
Cloud Vendor, Fuzzy Computations, Fuzzification, Cloud Service Provider, Cloud Clients, Authenticity.- Preventive Signature Model for Secure Cloud Deployment through Fuzzy Data Array Computation
Abstract Views :166 |
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.
- An Advanced Mechanism of Cloud Resource Security Process in Client Location by Using Soft Computing Approach
Abstract Views :295 |
PDF Views:4
Authors
Affiliations
1 SCSVMV University, Kanchipuram, Tamil Nadu, IN
1 SCSVMV University, Kanchipuram, Tamil Nadu, IN
Source
Journal of Applied Information Science, Vol 5, No 1 (2017), Pagination: 42-45Abstract
Cloud computing is providing the distinct set of services by the form of cloud resources to the client end location. It needs to be iterated and operated on the secured cloud platform. It will increase the lots of security controls, function elements to be protected in the in the cloud client end. Though numerous security procedures, components, data security options are exist, but still we need to improve the cloud resources. Whenever the clients will perform some set of cloud service transactions, it is mandatory to secure the login, security, attribute credentials for the concern users. It will be evaluated on the cloud user service access platform and also it increases the security rate of cloud services. The proposed approach will be the betterment of cloud service operations and the securing aspect of cloud service components in an effective way by making use of soft computing applications. Fuzzy based operational sequences, authentication techniques are adopted in the cloud security process.Keywords
Cloud Vendor, Fuzzy Technique, Cloud Server, Cloud Clients, Cloud Service Provider, Data Centre.References
- T. Truong-Huu, “A novel model for competition and cooperation among cloud providers,” IEEE Transactions on Cloud Computing, vol. 2, no. 3, pp. 251-265, 2014.
- A. Tchana, B. Dilenseger, N. De palma, J. Salmi, and A. Harbaoui, “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.
- L. Toma’s, and J. Tordsson, “An automatic approach to risk-aware data center overbooking,” IEEE Transactions on Cloud Computing, vol. 2, no. 3, 2014.
- Y. Wang, and W. 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.
- B. Guan, J. Wu, Y. Wang, and S. U. Khan, “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.
- S. Tang, B. Lee, and B. He, “Dynamic MR: A dynamic slot allocation optimization framework for Map reduce clusters” IEEE Transactions on Cloud Computing, vol. 2, no. 3, 2014.
- K. Konstanteli, T. Cucinotta, K. A. Psyches’, and T. Varvarigou, “Elastic admission control for federated cloud services,” IEEE Transactions on Cloud Computing, vol. 2, no. 3, pp. 348-361, July, 2014.
- S. Kailasam, P. Dhawalia, S. J. Balaji, G. Iyer, and J. Dharanipragada, “Extending Map-reduce across clouds with B-stream,” IEEE Transactions on Cloud Computing, vol. 2, no. 3, 362-376, July, 2014.
- S. Di, C. L. Wang, and F. Cappello, “Adaptive Algorithm for Minimizing Cloud Task Length with Prediction Errors,” IEEE Transactions on Cloud Computing, vol. 2, no. 2, April-June, 2014.
- S. Misra, S. Das, M. Khatua, S, and M. S. Obaidat, “Qos-guaranteed bandwidth shifting and redistribution in mobile cloud environment,” IEEE Transactions on Cloud Computing, vol. 2, no. 2, April-June, 2014.
- A. V. Dastjerdi, and R. Buyya, “Compatibility-Aware cloud service composition under fuzzy preferences of users,” IEEE Transactions on Cloud Computing, vol. 2, no. 1, January-March, 2014.
- H. Morshedlou, and M. R. Meybodi, “Decreasing impact of SLA violations: A proactive resource allocation approach for cloud computing environments,” IEEE Transactions on Cloud Computing, vol. 2, no. 2, April-June, 2014.
- Improving the Service Solutions on Hybrid Clouds at Edge Network using Fuzzy Approaches
Abstract Views :245 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, Tamil Nadu, IN
1 Department of CSE, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, Tamil Nadu, IN
Source
International Journal of Knowledge Based Computer System, Vol 6, No 1 (2018), Pagination: 7-11Abstract
So far in cloud computing environment, all the resources and services are used as an on-demand request basis from the client end. All typical service issues have been solved with the optimal cloud resource customization policies. The role of edge computing is enabling the data processing operations at the edge network which will operate in the cloud computing platforms. Due to increased amount of usage in the client location the proper devices need to be well connected with an internet. Edge mechanism is implemented in the real-time service based operation which will examine the upstream and downstream functional units will apply the real-time local data analysis in the data centre locations. The hybrid clouds will execute the service request form both the private cloud and public cloud users. These services and request based resources can be literally focused by the cloud service provider (CSP) and managed service provider (MSP) who will provide the cloud services uninterruptedly to the requested users. When the multiple services are executes in the edge network then the cloud vendor does not properly handle the services through the secured environment. Such kind of problem will lead the user to loss their control activities on the hybrid cloud solutions location. The proposed approaches of edge computing in hybrid cloud solutions are improving the service by applying the fuzzy logic control implementation factors. The cloud sim can be used as a simulator in the proposed model.Keywords
Cloud Service Provider, Cloud Sim, Cloud Vendor, Data Centre, Edge Network, Hybrid Clouds, Location Identity, Managed Service Provider, Process Segment Identity.References
- T. G. Rodrigues, and K. Suto, “Hybrid method for minimizing service delay in edge cloud computing through VM migration and transmission power control,” IEEE Transactions on Computers, vol. 66, no. 5, pp. 810-819, 2017.
- A. Rahman, and E. Hassanain, “Towards a secure mobile edge computing framework for Hajj,” IEEE Access, vol. 5, pp. 11768-11781, 2017.
- Z. Yan, and J. Xue, “Prius: Hybrid edge cloud and client adaptation for HTTP adaptive streaming in cellular networks,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 27, no. 1, pp. 209-222, 2017.
- K. Bhaskar, R. Jayashree, R. Sathiyavathi, L. M. Gladence, and V. M. Anu, “A novel approach for securing data de-duplication methodology in hybrid cloud storage,” International Conference on Innovations in Information Embedded and Communication Systems, pp. 1-5, 2017.
- L. Zuo, and L. Shu, “A multi-objective hybrid cloud resource scheduling method based on deadline and cost constraints”, IEEE Access, vol. 5, pp. 22067-22080, 2017.
- R. Garcia, “Federated identity hybrid cloud security considerations supporting first responders,” IEEE Conference on Dependable and Secure Computing, pp. 326-333, 2017
- C. Gopinaath, and A. Kiruthika, “A server side encryption for cloud storage with federation sharing in hybrid cloud environment,” International Conference on Technical Advancements in Computers and Communications, pp. 128-130, 2017.
- C. Hongbing, and R. Chunming, “Secure big data storage and sharing scheme for cloud tenants,” IEEE Transactions on Communication Systems, vol. 12, no. 6, 2015.
- J. Baek, and Q. H. Vu, “A secure cloud computing based framework for big data information management of smart grid,” IEEE Transactions on Cloud Computing, vol 3, no. 2, 2015.
- N. V. Juliadotter, and K. K. R. Choo, “Cloud attack and risk assessment taxonomy,” IEEE Transactions on Cloud Computing, vol. 2, no. 1, pp. 14-20, January-February 2015.
- Y. Xuanxia, H. Liu, H. Ning, L. T. Yang, and Y. Xiang, “Anonymous credential-based access control scheme for clouds,” IEEE Transactions on Cloud Computing, vol. 2, no. 4, pp. 34-43, 2015.
- H. Liu, and H. Ning, “Shared authority based privacy-preserving authentication protocol in cloud computing,” IEEE Transactions on Systems, vol. 26, no. 1, pp. 241-251, 2015.