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.

Software engineering and information security have traditionally followed divergent paths but lately some efforts have been made to consider security from the early phases of the Software Development Life Cycle (SDLC). This paper follows this line and concentrates on the incorporation of trust negotiations during the requirements engineering phase. More precisely, we provide an extension to the SI* modelling language, which is further formalised using answer set programming specifications to support the automatic verification of the model and the detection of privacy conflicts caused by trust negotiations.

The Internet of Things (IoT) is a paradigm based on the interconnection of everyday objects. It is expected that the ‘things’ involved in the IoT paradigm will have to interact with each other, often in uncertain conditions. It is therefore of paramount importance for the success of IoT that there are mechanisms in place that help overcome the lack of certainty. Trust can help achieve this goal. In this paper, we introduce a framework that assists developers in including trust in IoT scenarios. This framework takes into account trust, privacy and identity requirements as well as other functional requirements derived from IoT scenarios to provide the different services that allow the inclusion of trust in the IoT.

Trust negotiations are mechanisms that enable interaction between previously unknown users. After exchanging various pieces of potentially sensitive information, the participants of a negotiation can decide whether or not to trust one another. Therefore, trust negotiations bring about threats to personal privacy if not carefully considered. This paper presents a framework for representing trust negotiations in the early phases of the Software Development Life Cycle (SDLC). The framework can help software engineers to determine the most suitable policies for the system by detecting conflicts between privacy and trust requirements. More precisely, we extend the SI* modelling language and provide a set of predicates for defining trust and privacy policies and a set of rules for describing the dynamics of the system based on the established policies. The formal representation of the model facilitates its automatic verification. The framework has been validated in a distributed social network scenario for connecting drivers with potential passengers willing to share a journey.

In recent times, smart home devices like Amazon Echo and Google Home have reached mainstream popularity. These devices are intrinsically intrusive, being able to access user’s personal information. There are growing concerns about indiscriminate data collection and invasion of user privacy in smart home devices. Improper trust assumptions and security controls can lead to unauthorized access of the devices, which can have severe consequences (i.e. safety risks). In this paper, we analysed the behaviour of smart home devices with respect to trust relationships. We set up a smart home environment to evaluate how trust is built and managed. Then, we performed a number of interaction tests with different types of users (i.e. owner, guests). As a result, we were able to assess the effectiveness of the provided security controls and identify some relevant security issues. To address them, we defined a trust model and proposed a solution based on it for securing smart home devices.

Trust negotiation represents a suitable approach for building trust in online environments, where the interacting entities are anonymous. It covers important criteria on security and privacy. In this work, we propose a method for implementing our model specification that handles trust negotiation. We define the structure of the trust negotiation module that is a standalone unit capable of negotiating on its own. It may be included to any software by its defined interfaces. We realise our method with a ride-sharing scenario and four trust negotiation strategies that we apply in order to validate our design and implementation. We propose a solution that is fully customisable based on different requirements. The proposal provides guidelines for developers in the process of including trust negotiation into their software.

The Internet of Things (IoT) is a paradigm that permits smart entities to be interconnected anywhere and anyhow. IoT opens new opportunities but also rises new issues.
In this dynamic environment, trust is useful to mitigate these issues. In fact, it is important that the smart entities could know and trust the other smart entities in order to collaborate with them.
So far, there is a lack of research when considering trust through the whole System Development Life Cycle (SDLC) of a smart IoT entity.
In this paper, we suggest a new approach that considers trust not only at the end of the SDLC but also at the start of it. More precisely, we explore the modeling phase proposing a model-driven approach extending UML and SysML considering trust and its related domains, such as security and privacy.
We propose stereotypes for each diagram in order to give developers a way to represent trust elements in an effective way.
Moreover, we propose two new diagrams that are very important for the IoT: a traceability diagram and a context diagram.
This model-driven approach will help developers to model the smart IoT entities according to the requirements elicited in the previous phases of the SDLC.
These models will be a fundamental input for the following and final phases of the SDLC.