Biblio

Security must be a primary concern when engineering Future Internet (FI) systems and applications. In order to achieve secure solutions, we need to capture security requirements early in the Software Development Life Cycle (SDLC). Whereas the security community has traditionally focused on providing tools and mechanisms to capture and express hard security requirements (e.g. confidentiality), little attention has been paid to other important requirements such as trust and reputation. We argue that these soft security requirements can leverage security in open, distributed, heterogeneous systems and applications and that they must be included in an early phase as part of the development process. In this paper we propose a UML extension for specifying trust and reputation requirements, and we apply it to an eHealth case study.

Cloud sourcing consists of outsourcing data, services and infrastructure to cloud providers. Even when this outsourcing model brings advantages to cloud customers, new threats also arise as sensitive data and critical IT services are beyond customers' control. When an organization considers moving to the cloud, IT decision makers must select a cloud provider and must decide which parts of the organization will be outsourced and to which extent. This paper proposes a methodology that allows decision makers to evaluate their trust in cloud providers. The methodology provides a systematic way to elicit knowledge about cloud providers, quantify their trust factors and aggregate them into trust values that can assist the decision-making process. The trust model that we propose is based on trust intervals, which allow capturing uncertainty during the evaluation, and we define an operator for aggregating these trust intervals. The methodology is applied to an eHealth scenario.

Trust has become essential in computer science as a way of assisting the process of decision-making, such as access control. In any system, several tasks may be performed, and each of these tasks might pose different associated trust values between the entities of the system. For instance, in a file system, reading and overwriting a file are two tasks that pose different trust values between the users who can carry out these tasks. In this paper, we propose a simple model for automatically establishing trust relationships between entities considering an established order among tasks.

The Future Internet is posing new security challenges as their scenarios are bringing together a huge amount of stakeholders and devices that must interact under unforeseeable conditions. In addition, in these scenarios we cannot expect entities to know each other beforehand, and therefore, they must be involved in risky and uncertain collaborations. In order to minimize threats and security breaches, it is required that a well-informed decision-making process is in place, and it is here where trust and reputation can play a crucial role. Unfortunately, services and applications developers are often unarmed to address trust and reputation requirements in these scenarios. To overcome this limitation, we propose a trust and reputation framework that allows developers to create trust- and reputation-aware applications.  

The Future Internet (FI) comprises scenarios where many heterogeneous and dynamic entities must interact to provide services (e.g., sensors, mobile devices and information systems in smart city scenarios). The dynamic conditions under which FI applications must execute call for self-adaptive software to cope with unforeseeable changes in the application environment. Software engineering currently provides frameworks to develop reasoning engines that automatically take reconfiguration decisions and that support the runtime adaptation of distributed, heterogeneous applications. However, these frameworks have very limited support to address security concerns of these application, hindering their usage for FI scenarios. We address this challenge by enhancing self-adaptive systems with the concepts of trust and reputation. Trust will improve decision-making processes under risk and uncertainty, in turn improving security of self-adaptive FI applications. This paper presents an approach that includes a trust and reputation framework into a platform for adaptive, distributed component-based systems, thus providing software components with new abilities to include trust in their reasoning process.