Modelling, validating, and ranking of secure service compositions

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordIn the world of large-scale applications, software as a service (SaaS) in general and use of microservices, in particular, is bringing service-oriented architectures to a new level: Systems in general and systems that interact with human users (eg, sociotechnical systems) in particular are built by composing microservices that are developed independently and operated by different parties. At the same time, SaaS applications are used more and more widely by enterprises as well as public services for providing critical services, including those processing security or privacy of relevant data. Therefore, providing secure and reliable service compositions is increasingly needed to ensure the success of SaaS solutions. Building such service compositions securely is still an unsolved problem. In this paper, we present a framework for modelling, validating, and ranking secure service compositions that integrate both automated services as well as services that interact with humans. As a unique feature, our approach for ranking services integrates validated properties (eg, based on the result of formally analysing the source code of a service implementation) as well as contractual properties that are part of the service level agreement and, thus, not necessarily ensured on a technical level

Intruder deducibility constraints with negation. Decidability and application to secured service compositions

The problem of finding a mediator to compose secured services has been reduced in our former work to the problem of solving deducibility constraints similar to those employed for cryptographic protocol analysis. We extend in this paper the mediator synthesis procedure by a construction for expressing that some data is not accessible to the mediator. Then we give a decision procedure for verifying that a mediator satisfying this non-disclosure policy can be effectively synthesized. This procedure has been implemented in CL-AtSe, our protocol analysis tool. The procedure extends constraint solving for cryptographic protocol analysis in a significative way as it is able to handle negative deducibility constraints without restriction. In particular it applies to all subterm convergent theories and therefore covers several interesting theories in formal security analysis including encryption, hashing, signature and pairing.Comment: (2012

An extended ontology-based context model and manipulation calculus for dynamic web service processes

Services are oered in an execution context that is determined by how a provider provisions the service and how the user consumes it. The need for more exibility requires the provisioning and consumption aspects to be addressed at runtime. We propose an ontology-based context model providing a framework for service provisioning and consumption aspects and techniques for managing context constraints for Web service processes where dynamic context concerns can be monitored and validated at service process run-time. We discuss the contextualization of dynamically relevant aspects of Web service processes as our main goal, i.e. capture aspects in an extended context model. The technical contributions of this paper are a context model ontology for dynamic service contexts and an operator calculus for integrated and coherent context manipulation, composition and reasoning. The context model ontology formalizes dynamic aspects of Web services and facilitates reasoning. We present the context ontology in terms of four core dimensions - functional, QoS, domain and platform - which are internally interconnected

Access and information flow control to secure mobile web service compositions in resource constrained environments

The growing use of mobile web services such as electronic health records systems and applications like twitter, Facebook has increased interest in robust mechanisms for ensuring security for such information sharing services. Common security mechanisms such as access control and information flow control are either restrictive or weak in that they prevent applications from sharing data usefully, and/or allow private information leaks when used independently. Typically, when services are composed there is a resource that some or all of the services involved in the composition need to share. However, during service composition security problems arise because the resulting service is made up of different services from different security domains. A key issue that arises and that we address in this thesis is that of enforcing secure information flow control during service composition to prevent illegal access and propagation of information between the participating services. This thesis describes a model that combines access control and information flow control in one framework. We specifically consider a case study of an e-health service application, and consider how constraints like location and context dependencies impact on authentication and authorization. Furthermore, we consider how data sharing applications such as the e-health service application handle issues of unauthorized users and insecure propagation of information in resource constrained environments¹. Our framework addresses this issue of illegitimate information access and propagation by making use of the concept of program dependence graphs (PDGs). Program dependence graphs use path conditions as necessary conditions for secure information flow control. The advantage of this approach to securing information sharing is that, information is only propagated if the criteria for data sharing are verified. Our solution proposes or offers good performance, fast authentication taking into account bandwidth limitations. A security analysis shows the theoretical improvements our scheme offers. Results obtained confirm that the framework accommodates the CIA-triad (which is the confidentiality, integrity and availability model designed to guide policies of information security) of our work and can be used to motivate further research work in this field

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas