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dc.contributor.authorTari, Abdelkamel-
dc.contributor.authorYoucef, Samir-
dc.contributor.authorGodart, Claude-
dc.contributor.authorAhmed Nacer, Amina-
dc.date.accessioned2022-12-29T09:59:29Z-
dc.date.available2022-12-29T09:59:29Z-
dc.date.issued2017-
dc.identifier.citationGuellil, I., Saâdane, H., Azouaou, F., Gueni, B., & Nouvel, D. (2021). Arabic natural language processing: An overview. Journal of King Saud University-Computer and Information Sciences, 33(5), 497-507.en_US
dc.identifier.other2325-6362/17 $31.00 © 2017 IEEE DOI 10.1109/EDOC.2017.28-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4-
dc.descriptionCloud computing has emerged as a dominant technology because it avoids upfront infrastructure costs and helps organizations to focus on their core business activities, instead of their system infrastructure. In this context, some companies are willing to execute, in the same way as other software, their business processes (BP) in the cloud for enjoying its benefits. However, they are also reluctant for their more valuable software because of the new security risks the cloud introduces. Security risk can include many dimensions (privacy, integrity, availability . . . ). In this work, we focus on a particular aspect of security which is the privacy of a BP logic deployed on a multi-cloud for preventing a coalition of malicious clouds to re-construct important information by combining their BP logic knowledge. More precisely the paper presents a BP logic privacy metric to evaluate the risk a company has its BP logic hacked in a particular multi-cloud configuration. The global idea is that, on the one hand the more sensitive information is contained in some more sensitive BP fragments, and on the other hand, more these fragments are distant in a cloud configuration, more the configuration is resistant to privacy leaks. The distance between fragments is measured based on the number of clouds on the paths between sensitive fragments weighted with the reputation of these clouds. The metric considers not only attacks from one malicious cloud provider, but from a coalition of cloud providers.en_US
dc.description.abstractAbstract—Some companies are willing to execute their business processes (BP) in the cloud for enjoying its benefits. However, they are also reluctant because of the new security risks that using cloud resources introduces. Security risk includes many dimensions, but this work focus on preserving the privacy of the logic of a BP deployed in a multi-cloud context by preventing a coalition of malicious clouds to re-construct important information from this logic. More precisely, the paper presents a BP logic privacy metric directly supporting the evaluation of the risk a company has its logic hacked in a particular multi-cloud configuration Index terms— BP modelling, BP deployment in the cloud, Security risk, BP logic privacyen_US
dc.language.isoenen_US
dc.publisherIEEE 21st International Enterprise Distributed Object Computing Conferenceen_US
dc.relation.ispartofseriesaestin1;1-
dc.subjectMulti-Cloud Deploymenten_US
dc.subjectPrivacy Level of a Business Process Logicen_US
dc.titleA Metric for Evaluating the Privacy Level of a Business Process Logic in a Multi-Cloud Deploymenten_US
dc.typeOtheren_US
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