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DEVELOPING SECURE CLOUD APPLICATIONS.

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Title: DEVELOPING SECURE CLOUD APPLICATIONS.
Authors: RAK, MASSIMILIANO1, FICCO, MASSIMO1, BATTISTA, ERMANNO1, CASOLA, VALENTINA1, MAZZOCCA, NICOLA2
Source: Scalable Computing: Practice & Experience. Mar2014, Vol. 15 Issue 1, p49-63. 15p.
Subjects: Cloud storage, Application software security measures, Service level agreements
Abstract: Today the main limit to Cloud adoption is related to the perception of a security loss the users have. Indeed, the existing solutions to provide security are mainly focused on Cloud service provider prospective in order to securely integrate frameworks and Infrastructures as a Services in a Cloud datacenter. Customer could not monitor and evaluate the security mechanisms enforced by service provider. Service Level Agreements mainly focus on performance related terms and no guarantees are given for security mechanisms. Customers are interested in tools to verify and monitor the implemented security requirements. On the other hand, developers need tools to deploy Cloud applications offering measurable security grants to end users. In this paper, we propose an approach to implement security mechanisms as components in the application design process. We modeled security interactions according to the specific threat, the specific security requirements and user/application capabilities trying to improve security. It enables a Service Provider to offer security guarantees to customers. The approach has been designed to fit with different Cloud platforms, but to demonstrate its applicability, we will present a case study on the mOSAIC Platform. [ABSTRACT FROM AUTHOR]
Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="DE" term="%22Cloud+storage%22">Cloud storage</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software+security+measures%22">Application software security measures</searchLink><br /><searchLink fieldCode="DE" term="%22Service+level+agreements%22">Service level agreements</searchLink>
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  Data: Today the main limit to Cloud adoption is related to the perception of a security loss the users have. Indeed, the existing solutions to provide security are mainly focused on Cloud service provider prospective in order to securely integrate frameworks and Infrastructures as a Services in a Cloud datacenter. Customer could not monitor and evaluate the security mechanisms enforced by service provider. Service Level Agreements mainly focus on performance related terms and no guarantees are given for security mechanisms. Customers are interested in tools to verify and monitor the implemented security requirements. On the other hand, developers need tools to deploy Cloud applications offering measurable security grants to end users. In this paper, we propose an approach to implement security mechanisms as components in the application design process. We modeled security interactions according to the specific threat, the specific security requirements and user/application capabilities trying to improve security. It enables a Service Provider to offer security guarantees to customers. The approach has been designed to fit with different Cloud platforms, but to demonstrate its applicability, we will present a case study on the mOSAIC Platform. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Mar2014
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