2,133 research outputs found

    Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

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    Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

    A sensitive data access model in support of learning health systems

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    Given the ever-growing body of knowledge, healthcare improvement hinges more than ever on efficient knowledge transfer to clinicians and patients. Promoted initially by the Institute of Medicine, the Learning Health System (LHS) framework emerged in the early 2000s. It places focus on learning cycles where care delivery is tightly coupled with research activities, which in turn is closely tied to knowledge transfer, ultimately injecting solid improvements into medical practice. Sensitive health data access across multiple organisations is therefore paramount to support LHSs. While the LHS vision is well established, security requirements to support them are not. Health data exchange approaches have been implemented (e.g., HL7 FHIR) or proposed (e.g., blockchain-based methods), but none cover the entire LHS requirement spectrum. To address this, the Sensitive Data Access Model (SDAM) is proposed. Using a representation of agents and processes of data access systems, specific security requirements are presented and the SDAM layer architecture is described, with an emphasis on its mix-network dynamic topology approach. A clinical application benefiting from the model is subsequently presented and an analysis evaluates the security properties and vulnerability mitigation strategies offered by a protocol suite following SDAM and in parallel, by FHIR

    Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments

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    Decentralized systems are a subset of distributed systems where multiple authorities control different components and no authority is fully trusted by all. This implies that any component in a decentralized system is potentially adversarial. We revise fifteen years of research on decentralization and privacy, and provide an overview of key systems, as well as key insights for designers of future systems. We show that decentralized designs can enhance privacy, integrity, and availability but also require careful trade-offs in terms of system complexity, properties provided, and degree of decentralization. These trade-offs need to be understood and navigated by designers. We argue that a combination of insights from cryptography, distributed systems, and mechanism design, aligned with the development of adequate incentives, are necessary to build scalable and successful privacy-preserving decentralized systems

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

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    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

    Towards a Network-based Approach for Smartphone Security

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    Smartphones have become an important utility that affects many aspects of our daily life. Due to their large dissemination and the tasks that are performed with them, they have also become a valuable target for criminals. Their specific capabilities and the way they are used introduce new threats in terms of information security. The research field of smartphone security has gained a lot of momentum in the past eight years. Approaches that have been presented so far focus on investigating design flaws of smartphone operating systems as well as their potential misuse by an adversary. Countermeasures are often realized based upon extensions made to the operating system itself, following a host-based design approach. However, there is a lack of network-based mechanisms that allow a secure integration of smartphones into existing IT infrastructures. This topic is especially relevant for companies whose employees use smartphones for business tasks. This thesis presents a novel, network-based approach for smartphone security called CADS: Context-related Signature and Anomaly Detection for Smartphones. It allows to determine the security status of smartphones by analyzing three aspects: (1) their current configuration in terms of installed software and available hardware, (2) their behavior and (3) the context they are currently used in. Depending on the determined security status, enforcement actions can be defined in order to allow or to deny access to services provided by the respective IT infrastructure. The approach is based upon the distributed collection and central analysis of data about smartphones. In contrast to other approaches, it explicitly supports to leverage existing security services both for analysis and enforcement purposes. A proof of concept is implemented based upon the IF-MAP protocol for network security and the Google Android platform. An evaluation verifies (1) that the CADS approach is able to detect so-called sensor sniffing attacks and (2) that reactions can be triggered based on detection results to counter ongoing attacks. Furthermore, it is demonstrated that the functionality of an existing, host-based approach that relies on modifications of the Android smartphone platform can be mimicked by the CADS approach. The advantage of CADS is that it does not need any modifications of the Android platform itself
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