14,829 research outputs found

    Fog Computing: A Taxonomy, Survey and Future Directions

    Full text link
    In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

    Secure Cloud-Edge Deployments, with Trust

    Get PDF
    Assessing the security level of IoT applications to be deployed to heterogeneous Cloud-Edge infrastructures operated by different providers is a non-trivial task. In this article, we present a methodology that permits to express security requirements for IoT applications, as well as infrastructure security capabilities, in a simple and declarative manner, and to automatically obtain an explainable assessment of the security level of the possible application deployments. The methodology also considers the impact of trust relations among different stakeholders using or managing Cloud-Edge infrastructures. A lifelike example is used to showcase the prototyped implementation of the methodology

    Community-Based Security for the Internet of Things

    Full text link
    With more and more devices becoming connectable to the internet, the number of services but also a lot of threats increases dramatically. Security is often a secondary matter behind functionality and comfort, but the problem has already been recognized. Still, with many IoT devices being deployed already, security will come step-by-step and through updates, patches and new versions of apps and IoT software. While these updates can be safely retrieved from app stores, the problems kick in via jailbroken devices and with the variety of untrusted sources arising on the internet. Since hacking is typically a community effort? these days, security could be a community goal too. The challenges are manifold, and one reason for weak or absent security on IoT devices is their weak computational power. In this chapter, we discuss a community based security mechanism in which devices mutually aid each other in secure software management. We discuss game-theoretic methods of community formation and light-weight cryptographic means to accomplish authentic software deployment inside the IoT device community

    A privacy‐preserving framework for smart context‐aware healthcare applications

    Get PDF
    Internet of things (IoT) is a disruptive paradigm with wide ranging applications including healthcare, manufacturing, transportation and retail. Within healthcare, smart connected wearable devices are widely used to achieve improved wellbeing, quality of life and security of citizens. Such connected devices generate significant amount of data containing sensitive information about patient requiring adequate protection and privacy assurance. Unauthorized access to an individual’s private data constitutes a breach of privacy leading to catastrophic outcomes for an individuals personal and professional life. Furthermore, breach of privacy may also lead to financial loss to the governing body such as those proposed as part of the General Data Protection Regulation (GDPR) in Europe. Furthermore, while mobility afforded by smart devices enables ease of monitoring, portability and pervasive processing, it also introduces challenges with respect to scalability, reliability and context-awareness for its applications. This paper is focused on privacy preservation within smart context-aware healthcare with a special emphasis on privacy assurance challenges within the Electronic Transfer of Prescription (ETP). To this extent, we present a case for a comprehensive, coherent, and dynamic privacypreserving system for smart healthcare to protect sensitive user data. Based on a thorough analysis of existing privacy preservation models we propose an enhancement for the widely used Salford model to achieve privacy preservation against masquerading and impersonation threats. The proposed model therefore improves privacy assurance for cutting edge IoT applications such as smart healthcare whilst addressing unique challenges with respect to context-aware mobility of such applications
    • 

    corecore