Open authorization (OAuth) is an open protocol, which allows secure authorization in a simple and standardized way from third-party applications accessing online services, based on the representational state transfer (REST) web architecture. OAuth has been designed to provide an authorization layer, typically on top of a secure transport layer such as HTTPS. The Internet of Things (IoTs) refers to the interconnection of billions of resource-constrained devices, denoted as smart objects, in an Internet-like structure. Smart objects have limited processing/memory capabilities and operate in challenging environments, such as low-power and lossy networks. IP has been foreseen as the standard communication protocol for smart object interoperability. The Internet engineering task force constrained RESTful environments working group has defined the constrained application protocol (CoAP) as a generic web protocol for RESTful-constrained environments, targeting machine-to-machine applications, which maps to HTTP for integration with the existing web. In this paper, we propose an architecture targeting HTTP/CoAP services to provide an authorization framework, which can be integrated by invoking an external oauth-based authorization service (OAS). The overall architecture is denoted as IoT-OAS. We also present an overview of significant IoT application scenarios. The IoT-OAS architecture is meant to be flexible, highly configurable, and easy to integrate with existing services. Among the advantages achieved by delegating the authorization functionality, IoT scenarios benefit by: 1) lower processing load with respect to solutions, where access control is implemented on the smart object; 2) fine-grained (remote) customization of access policies; and 3) scalability, without the need to operate directly on the device.

The Internet of Things (IoT) aims at connecting billions of devices in an Internet-like structure. This gigantic information exchange enables new opportunities and new forms of interactions among things and people. A crucial enabler of robust applications and easy smart objects' deployment is the availability of mechanisms that minimize (ideally, cancel) the need for external human intervention for configuration and maintenance of deployed objects. These mechanisms must also be scalable, since the number of deployed objects is expected to constantly grow in the next years. In this work, we propose a scalable and self-configuring peer-to-peer (P2P)-based architecture for large-scale IoT networks, aiming at providing automated service and resource discovery mechanisms, which require no human intervention for their configuration. In particular, we focus on both local and global service discovery (SD), showing how the proposed architecture allows the local and global mechanisms to successfully interact, while keeping their mutual independence (from an operational viewpoint). The effectiveness of the proposed architecture is confirmed by experimental results obtained through a real-world deployment.

The application of Internet of Things (IoT) within industrial environments is fostering the adoption of the Digital Twin (DT) approach, applied at the edge of the network to handle heterogeneity stemming from siloed application management solutions and from protocols originated by different manufacturing tools and enterprise services. In this challenging context, network heterogeneity also represents a critical element that can significantly limit the design and deployment of DT-oriented applications. The paper proposes the Application-driven Digital Twin Networking (ADTN) middleware with the twofold objective of: (1) Simplifying the interaction among heterogeneous devices by allowing DTs to exploit IP-based protocols instead of specialized industrial ones and to enhance packet content expressiveness, by enriching data via well-defined standards. (2) Dynamically managing network resources in edge industrial environments, applying Software Defined Networking (SDN) to exploit the communication mechanisms most suitable to application requirements, ranging from native IP to more articulated based on packet content.

In recent years, digital twins have been pervading different application domains—from manufacturing to healthcare—as an approach for virtualising different kinds of physical entities (things, products, machines). The dominant view developed in the literature so far is about the virtualisation of individual physical assets in a closed-system perspective. In this article, we introduce and explore a broader perspective that we call Web of Digital Twins (WoDT), in which the digital twin paradigm is exploited for the pervasive softwarisation of possibly large-scale interrelated physical realities. A WoDT can be conceived as an open, distributed and dynamic ecosystem of connected digital twins, functioning as an interoperable service-oriented layer for applications running on top, especially smart applications and multiagent systems. The article introduces an abstract model and architecture aimed to capture key aspects of the idea not bound to any specific application domains or implementing technologies and discusses their adoption in engineering real-world systems. To this purpose, two concrete case studies are considered, in the context of healthcare and smart mobility. Finally, the article includes a discussion of a selected set of research directions.

Application markets have revolutionized the software download model of mobile phones: third-party application developers offer software on the market that users can effortlessly install on their phones. This great step forward, however, also imposes some threats to user privacy: applications often ask for permissions that reveal private information such as the user's location, contacts and messages. While some mechanisms to prevent leaks of user privacy to applications have been proposed by the research community, these solutions fail to consider that application markets are primarily driven by advertisements that rely on accurately profiling the user. In this paper we take into account that there are two parties with conflicting interests: the user, interested in maintaining their privacy and the developer who would like to maximize their advertisement revenue through user profiling. We have conducted an extensive analysis of more than 250,000 applications in the Android market. Our results indicate that the current privacy protection mechanisms are not effective as developers and advert companies are not deterred. Therefore, we designed and implemented a market-aware privacy protection framework that aims to achieve an equilibrium between the developer's revenue and the user's privacy. The proposed framework is based on the establishment of a feedback control loop that adjusts the level of privacy protection on mobile phones, in response to advertisement generated revenue.

IoT systems based on Digital Twins (DTs) — virtual copies of physical objects and systems — can be very effective to enable data-driven services and promote better control and decisions, in particular by exploiting distributed approaches where cloud and edge computing cooperate effectively. In this context, digital twins deployed on the edge represents a new strategic element to design a new wave of distributed cyber-physical applications. Existing approaches are generally focused on fragmented and domain-specific monolithic solutions and are mainly associated to model-driven, simulative or descriptive visions. The idea of extending the DTs role to support last-mile digitalization and interoperability through a set of general purpose and well-defined properties and capabilities is still underinvestigated. In this paper, we present the novel Edge Digital Twins (EDT) architectural model and its implementation, enabling the lightweight replication of physical devices providing an efficient digital abstraction layer to support the autonomous and standard collaboration of things and services. We model the core capabilities with respect to the recent definition of the state of the art, present the software architecture and a prototype implementation. Extensive experimental analysis shows the obtained performance in multiple IoT application contexts and compares them with that of state-of-the-art approaches.