Biblio

In this paper we tackle the problem of privacy and confidentiality in Identity Management as a Service (IDaaS). The adoption of cloud computing technologies by organizations has fostered the externalization of the identity management processes, shaping the concept of Identity Management as a Service. However, as it has happened to other cloud-based services, the cloud poses serious risks to the users, since they lose the control over their data. As part of this work, we analyze these concerns and present a model for privacy-preserving IDaaS, called BlindIdM, which is designed to provide data privacy protection through the use of cryptographic safeguards.

In this paper we tackle the problem of privacy and confidentiality in Identity Management as a Service (IDaaS). The adoption of cloud computing technologies by organizations has fostered the externalization of the identity management processes, shaping the concept of Identity Management as a Service. However, as it has happened to other cloud-based services, the cloud poses serious risks to the users, since they lose the control over their data. As part of this work, we analyze these concerns and present a model for privacy-preserving IDaaS, called BlindIdM, which is designed to provide data privacy protection through the use of cryptographic safeguards.

Cloud computing is becoming a key IT infrastructure technology being adopted progressively by companies and users. Still, there are issues and uncertainties surrounding its adoption, such as security and how users data is dealt with that require attention from developers, researchers, providers and users. The A4Cloud project tries to help solving the problem of accountability in the cloud by providing tools that support the process of achieving accountability. This paper presents the contents of the first A4Cloud tutorial. These contents include basic concepts and tools developed within the project. In particular, we will review how metrics can aid the accountability process and some of the tools that the A4Cloud project will produce such as the Data Track Tool (DTT) and the Cloud Offering Advisory Tool (COAT).

Cloud computing is becoming a key IT infrastructure technology being adopted progressively by companies and users. Still, there are issues and uncertainties surrounding its adoption, such as security and how users data is dealt with that require attention from developers, researchers, providers and users. The A4Cloud project tries to help solving the problem of accountability in the cloud by providing tools that support the process of achieving accountability. This paper presents the contents of the first A4Cloud tutorial. These contents include basic concepts and tools developed within the project. In particular, we will review how metrics can aid the accountability process and some of the tools that the A4Cloud project will produce such as the Data Track Tool (DTT) and the Cloud Offering Advisory Tool (COAT).

Cloud applications entail the provision of a huge amount of heterogeneous, geographically-distributed resources managed and shared by many different stakeholders who often do not know each other beforehand. This raises numerous security concerns that, if not addressed carefully, might hinder the adoption of this promising computational model. Appropriately dealing with these threats gains special relevance in the social cloud context, where computational resources are provided by the users themselves. We argue that taking trust and reputation requirements into account can leverage security in these scenarios by incorporating the notions of trust relationships and reputation into them. For this reason, we propose a development framework onto which developers can implement trust-aware social cloud applications. Developers can also adapt the framework in order to accommodate their application-specific needs.

Cloud governance, and in particular data governance in the cloud, relies on different technical and organizational practices and procedures, such as policy enforcement, risk management, incident management and remediation. The concept of accountability encompasses such practices, and is essential for enhancing security and trustworthiness in the cloud. Besides this, proper measurement of cloud services, both at a technical and governance level, is a distinctive aspect of the cloud computing model. Hence, a natural problem that arises is how to measure the impact on accountability of the procedures held in practice by organizations that participate in the cloud ecosystem. In this paper, we describe a metamodel for addressing the problem of measuring accountability properties for cloud computing, as discussed and defined by the Cloud Accountability Project (A4Cloud). The goal of this metamodel is to act as a language for describing: (i) accountability properties in terms of actions between entities, and (ii) metrics for measuring the fulfillment of such properties. It also allows the recursive decomposition of properties and metrics, from a high-level and abstract world to a tangible and measurable one. Finally, we illustrate our proposal of the metamodel by modelling the transparency property, and define some metrics for it.

Cloud governance, and in particular data governance in the cloud, relies on different technical and organizational practices and procedures, such as policy enforcement, risk management, incident management and remediation. The concept of accountability encompasses such practices, and is essential for enhancing security and trustworthiness in the cloud. Besides this, proper measurement of cloud services, both at a technical and governance level, is a distinctive aspect of the cloud computing model. Hence, a natural problem that arises is how to measure the impact on accountability of the procedures held in practice by organizations that participate in the cloud ecosystem. In this paper, we describe a metamodel for addressing the problem of measuring accountability properties for cloud computing, as discussed and defined by the Cloud Accountability Project (A4Cloud). The goal of this metamodel is to act as a language for describing: (i) accountability properties in terms of actions between entities, and (ii) metrics for measuring the fulfillment of such properties. It also allows the recursive decomposition of properties and metrics, from a high-level and abstract world to a tangible and measurable one. Finally, we illustrate our proposal of the metamodel by modelling the transparency property, and define some metrics for it.