An Efficient Framework for Cloud Infrastructure Security
| Autor: | Prasanna Balaji Narasingapuram, M. Ponnavaikko |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies Multitenancy Computer science business.industry Data_MISCELLANEOUS Control (management) 0211 other engineering and technologies Botnet Denial-of-service attack Cloud computing 02 engineering and technology Computer security computer.software_genre Shared resource Resource (project management) 0202 electrical engineering electronic engineering information engineering Entropy (information theory) 020201 artificial intelligence & image processing business computer |
| Zdroj: | 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS). |
| DOI: | 10.1109/iciss49785.2020.9316069 |
| Popis: | Cloud Computing has developed as another worldview in which users can use on-request services, as per their requirements. Be that as it may, security concerns are essential hindrances to a more extensive appropriation of clouds. Recently conceived ideas that clouds presented, for example, multitenancy, resource sharing and redistributing, make new difficulties for the security research. DDoS (Distributed Denial of service) attack is the greatest danger to the cloud since it influences the accessibility of services. To identify the attack on every worker, an indicator is sent that utilizes an entropy-based methodology for detecting DDoS. A critical deviation in entropy speaks to the DDoS attack. Inorder to shield the cloud climate from malicious users, we proposed a novel trust based admittance control model. This model approves the client dependent on client trust esteem, before getting to the cloud resources. The client must be trusted before getting to the resources and the resources must be trusted before offering the support to the client. On the off chance that the trust estimation of both client and cloud resource are more than their trust limit esteem, at that point they are viewed as trusted. Simulation results show that proposed model performs in a way that is better than comparative models as far as rightness of result. |
| Databáze: | OpenAIRE |
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