- Mohammad Rifat Ahmmad RASHID, Davide CONZON, Xu TAO and Enrico FERRERA
- Published in the book “Security and Privacy in Internet of Things: Challenges and Solutions”
Authors: E. Ferrera, C.Pastrone et al.
Category: Book chapter in “Next Generation Internet of Things, Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation, 2018”
The chapter presents an overview of the eight that are part of the European IoT Security and Privacy Projects initiative (IoT-ESP) addressing advanced concepts for end-to-end security in highly distributed, heterogeneous and dynamic IoT environments. The approaches presented are holistic and include identification and authentication, data protection and prevention against cyber-attacks at the device and system levels. The projects present architectures, concepts, methods and tools for open IoT platforms integrating evolving sensing, actuating, energy harvesting, networking and interface technologies. Platforms should provide connectivity and intelligence, actuation and control features, linkage to modular and ad-hoc cloud services, The IoT platforms used are compatible with existing international developments addressing object identity management, discovery services, virtualisation of objects, devices and infrastructures and trusted IoT approaches.
Authors: Diego Fernández, Ricardo Váquez, Román Maceiras y Adriel Regueira.
In this article, the authors present the results of testing a solution that could allow the integration of sensor systems and platforms within the EMALCSA infrastructure, identifying correlations between the obtained values and the existing platforms and infrastructure. For this purpose, the framework developed in BRAIN-IoT is implemented, to enable interoperability between the current management and control system with other existing IoT platforms and open-source initiatives in a decentralized manner. The distributed nature of the IoT makes it necessary for the BRAIN-IoT platform to ensure good security practices and with privacy and data integrity policies.
- Authors: Davide Conzon, Mohammad Rifat Ahmmad Rashid, Xu Tao, Angel Soriano, Robotnik Automation, Richard Nicholson, Enrico Ferrera
- Published in: 2019 4th International Conference on Computing, Communications and Security (ICCCS)
- Authors: Richard Nicholson, Timothy Ward, Derek Baum, Xu Tao, Davide Conzon and Enrico Ferrera
- Jul. 2019, World Conference on Smart Trends in Systems, Security and Sustainability
The next generation of Smart City and Industry 4.0 applications will be geographically distributed, heterogeneous, co-evolving software ecosystems, significantly more sophisticated than the current Enterprise or Cloud compute environments. To be economically sustainable and achieve solution longevity, these software ecosystems must be operationally simple, cost effective to maintain over extended periods of time, and able to cost effectively adapt to both changing environmental conditions and service requirements. This paper presents the BRAIN-IoT Federation, a distributed and highly modular federated environment that addresses these sustainability, longevity and adaptability challenges by leveraging OSGi – the Open Standard for Software Modularity. With a focus on Operational simplicity, BRAIN-IoT federation enables the dynamic deployment, orchestration and monitoring of distributed applications and uniquely, automatically installing new behaviours in response to environment triggers and User events. To show how, through the use of OSGi components and standards, it is possible to build a software solution able to address all the challenges presented by the modern scenarios, in terms of agility and adaptability, this work presents an use case study related to the use of robots for last-mile delivery of parcels. Over the next few years this field promises to provide high cost savings and reduction of the environmental impact, allowing to reduce the traffic caused by parcels delivering. An exploration of how the BRAIN-IoT federation is applicable to such environment, enabling robots adapt to changing and diverse Internet of Things environments, will be presented in the paper.
- Authors: Rim El Ballouli, Saddek Bensalem, Marius Bozga, and Joseph Sifakis
- April 2019, MeTRID 2019: 2nd International workshop on Methods and Tools for Rigorous System Design
- Four Exercises in Programming Dynamic Reconfigurable Systems: Methodology and Solution in DR-BIP
- Presentation: Slides
- Jacques Combaz
- April 2019, MeTRID 2019: 2nd International workshop on Methods and Tools for Rigorous System Design
- Author: Saddek Bensalem
- February 2019, Dagstuhl-Seminar 1908, “Verification and Synthesis of Human-Robot Interaction”
- Authors: E. Ferrera, C.Pastrone et al.
- Book chapter: Next Generation Internet of Things, Distributed Intelligence at the Edge and Human Machine-to-Machine Cooperation, 2018
- Pages 209-221
- Statistical Model Checking BIP tool [link is missing]
- Saddek Bensalem
- June 2019, Workshop on Trustworthy Embedded Software organized by Huawei
- Rigorous System Design: The BIP framework [link is missing]
- Saddek Bensalem
- November 2019, Proposed lectures to the Doctoral School (EMSTII) of UGA.
- Duration: 12 hours
- Number of PhD students : around 15.
- BRAIN-IoT: Paving The Way For Next-Generation Internet of Things [link is missing]
- Enrico Ferrera, Xu Tao, Davide Conzon, Victor Sonora Pombo, Miquel Cantero, Tim Ward, Ilaria Bosi, Mirko Sandretto
- May 2020, Accepted at the AIinIoT – Workshop on Next Generation Internet of Things, co-located with the IoTBDS2020 conference.
The main objective of work package 7 is to create awareness and adoption of the BRAIN-IoT project within the targeted communities defined by deliverables D7.4 & D7.1, i.e.: Research Communities, Developer Communities (Early adopters and Late adopters), Solution makers, End users and the general public
This report documents the initial efforts and results of the project in term of advertising and community engagement. It follows the dissemination strategy defined in D7.1.
In this document, a list of the press releases, articles, social media tools and available contents will be presented, as well as a brief summary of the events in which the project has participated.
This deliverable documents the activities related to the website of the Brain-IoT project, the main tool to communicate project results to scientists, scholars, professionals, the interested public and other stakeholders. More specifically, it aims at providing a project introduction as well as continuous updates on project results. The website is designed using the WordPress Content Management System (CMS), as it naturally supports the combination of static pages with blog entries that are continuously added. WordPress also provides an editorial system that supports the coordination of inputs from the different partners and collaborators of the project.
This document defines the project‘s outreach strategy including an effective communication plan. The strategy is intended to optimize dissemination of project knowledge and results to scientific, open source and industrial communities, companies and public organizations. This document will identify the main stakeholders‘ communities to be mobilized by the project and for each define the best media, events, and publications to target.
This document will be a living document throughout the project regularly updated to take count of strategy evolutions. The evolution of the strategy will be visible in the next deliverables D7.3, D7.5 and D7.6 which will present an update of the Advertising, Community Engagement materials and Results.
This document is split in three main sections:
- How we identify our customers, describing the projects’ efforts to identify the dissemination and exploitations targets, i.e. the project “customers”.
- The Dissemination strategy outlining the dissemination activities carried out by the BRAIN-IoT project partners.
- The Eclipse IoT Proposal explaining the benefits in joining an open source community like the Eclipse Foundation and explaining the steps the BRAIN-IoT project proposal has to go through to be sustainable in this open source community.
The purpose of this document is to present the initial Data Management Plan (DMP) of the BRAIN-IoT project and to provide the guidelines for maintaining the DMP during the project.
The Data Management Plan methodology approach adopted for the compilation of D6.1 has been based on the updated version of the “Guidelines on FAIR Data Management in Horizon 2020 version 3.0 released on 26 July 2016 by the European Commission Directorate – General for Research & Innovation”. It defines how data in general and research data in particular will be handled during the research project and will make suggestions for the after-project time. It describes what data will be collected, processed or generated within the scope of the project, what methodologies and standards shall be followed during the collection process, whether and how these data shall be shared and/or made open for the evaluation needs, and how they shall be curated and preserved.
All BRAIN-IoT data will be handled according to EU Data protection and Privacy regulation and the General Data Protection Regulation (GDPR).
Deliverable D3.1 is aiming to design a BRAIN-IoT modelling language IoT-ML which allows to virtualize concrete physical world devices including also complex system such as autonomous robots and critical control devices, as well as data and capabilities models for cross-platform interoperability. The main challenge in this work is to design a IoT Modelling language which can embrace multiple domains. The framework designed could provide the capability to model several different aspects, meaning it could support several individual modelling approaches as well as modelling languages.
This document explores how BRAIN-IoT approaches the requirements of initial device discovery, search, composition and orchestration in a manner that addresses these non-functional challenges. The proposed approach is sufficiently flexible to deal with any foreseeable runtime use case and this document maps out a strategy to deliver this. However, it should also be noted that current BRAIN-IoT Use Case(s) will be subsets of these generalised behaviours.
This document reports on the initial threat modeling and security assessment of the BRAIN-IoT proposed scenarios and the followed security methodology which is based on known threats analyzed by international initiatives undergoing in the EU and worldwide. Starting from the scenarios and architectural solutions defined by WP2, the authors performed an initial analysis considering intentional threats that may result in BRAIN-IoT services to be compromised or disrupted.
This document represents the first iteration of the BRAIN-IoT architecture with focus on: i) identifying BRAIN-IoT things and platforms, ii) defining initial set of requirements, iii) defining initial version of the BRAIN-IoT reference architecture, iv) identifying BRAIN-IoT relevant technologies, v) defining Proof-of-Concept specifications.
The reference architecture and the requirement list in this deliverable will be revised, extended and refined in the next iteration.
Initial version of the vision, application scenarios and use cases in which the results of the BRAIN-IoT project will be demonstrated. D2.1 work has been conducted using domain analysis and brainstorming sessions involving relevant stakeholders and use case analyses. This document reports on the iterative process of ideation which resulted in the definition of: 1) the workflow of the workbench, 2) an initial set of relevant stakeholders, 3) the communication flow between them, and 4) the initial set of use cases.
The official BRAIN-IoT flyer and poster are available below, please feel free to download them!
- BRAIN-IoT – The Evolvable Software Nervous System for Tomorrow’s Autonomous Smart Cities and Industry 4.0 (PAREMUS)
- Eclipse Foundation supports EU funded Brain-IoT Project
- IDATE DigiWorld has been selected to Provide Market Analysis and Exploitation Support for EU funded IoT Research Project
- Airbus CyberSecurity brings its expertise to EU funded Brain-IoT Project
Other Press Release