End-to-end security for IoT
  • Authors:  Paul-Emmanuel Brun, Guillemette Massot (AIRBUS Cybersecurity)
  • Location: John Soldatos (ed.) (2020), “Security Risk Management for the Internet of Things: Technologies and Techniques for IoT Security, Privacy and Data Protection”, Boston-Delft: now publishers, Pages 208-219

Abstract: According to market forecasts, IoT products and services are spreading very quickly in all professional and mass-market usage scenarios in terms of revenues and volumes of devices and services. In the meantime, lots of pilots and commercial deployments are demonstrating the added value of IoT-based solutions in real scale, and in all market segments, from the transportation industry to the utility sector but also in smart building, factory of the future, or healthcare applications. The use of historical and live data in big data lakes will allow recognizing anomalies, implementing alert functions, calculating solutions and optimizations for a more efficient digitalized world. In order to build trustable services and solutions, devices information needs to be trusted. This can only be ensured if IoT systems are end to end protected, ensuring protection against corrupted third parties. Indeed, while state of-the-art IT communication protocols such as HTTPS ensure end-to-end security, many IoT communication protocols have strong constraints in terms of bandwidth, power, and computation capabilities that do not fit state-of-the-art security protocols. In this context, BRAIN-IoT project has tested an innovative approach to ensure end-to-end security on constrained protocols with limited impact on bandwidth and power consumption.

Asset-Driven Approach for Security Risk Assessment in IoT Systems

Abstract:  The growth of damage caused by security issues in IoT-based systems requires the definition of a rigorous methodology allowing risks assessment and protecting the system against them. In this work, we propose an approach that follows the security standards to identify and analyse the potential risks. Our approach starts by specifying the system assets considering IoT domain model and the potential threats that might compromise them. Starting from the list of threats, we define the security objectives then technical requirements and countermeasures that can cover these objectives. We apply our approach to an IoT system for monitoring and control the management of the urban water cycle.

Rigorous System Design: The BIP framework
  • Author: Saddek Bensalem
  • Location: November 2019, Proposed lectures to the Doctoral School (EMSTII) of UGA.
  • Duration: 12 hours
  • Number of PhD students: around 15
Statistical Model Checking BIP tool
  • Author: Saddek Bensalem
  • Location: June 2019, Workshop on Trustworthy Embedded Software organized by Huawei
Privacy Awareness, Risk Assessment, and Control Measures in IoT Platforms: BRAIN-IoT Approach
  • Authors: Mohammad Rifat Ahmmad Rashid, Xu Tao, Davide Conzon, and Enrico Ferrera
  • Location: In book: “Security Risk Management for the Internet of Things: Technologies and Techniques for IoT Security, Privacy and Data Protection”

Abstract: With the increasing adaptation of IoT platforms in decentralized cloud environments, more focus has been given towards facilitating the privacy awareness building upon goals set by current European Union (EU) GDPR regulations. Therefore, it is necessary to empower the end users (both private and corporate) of IoT platforms with the capability of deciding which combination of self-hosted or cloud-oriented IoT systems is most suitable to handle the personal data they generate and own as well as with the ability to change the existing (or preset) configurations at any time. BRAIN-IoT platform focuses on complex scenarios where actuation and control are cooperatively supported by populations of IoT systems. The breakthrough targeted by BRAIN-IoT is to provide solutions to embed privacy awareness and privacy control features in IoT solutions. In this work, the authors explore the following key areas: (a) privacy awareness in IoT systems using GDPR regulations and BRAIN-IoT platform, and (b) propose a conceptual framework for PIA using privacy principles presented in GDPR regulations.

Model-Based Methodology and Framework for Design and Management of Next-Gen IoT Systems

Abstract: Internet of Things (IoT) is a pervasive technology covering many applications areas (Smart Mobility, Smart Industry, Smart Healthcare, Smart Building, etc.). Its success and the technology evolution allow targeting more complex and critical applications such as the management of critical infrastructures and cooperative service robotics, which requires real time operation and a higher level of intelligence in the monitoring-control command for decision-making. Furthermore, these applications type need to be fully validated in advance considering that bugs discovered during real operation could cause significant damages. In order to avoid these drawbacks, IoT developers and system integrators need advanced tools and methodologies. This paper presents a methodology and a set of tools, defined and developed in the context of the BRAIN-IoT European Union (EU) project. The overall framework includes both Open semantic models to enforce interoperable operations and exchange of data and control features; and Model-based development tools to implement Digital Twin solutions to facilitate the prototyping and integration of interoperable and reliable IoT system solutions. After describing the solution developed, this paper also presents concrete use cases based on the two critical systems mentioned above, leveraging the application scenarios used to validate the concepts developed and results obtained by the BRAIN-IoT project.

A Cross-Platform Communication Mechanism for ROS-Based Cyber-Physical System

Abstract: Recently, one of the main research topics in the context of application of Cyber-Physical System (CPS) in the Smart City and Industry 4.0 scenarios is the one related to the use of Robot Operating System (ROS)-based CPS. Specifically, one of the main interest is to allow a ROS-based smart robot communicating with other heterogeneous Internet of Things (IoT) applications in an intelligent environment to efficiently react to the system requirements and environment changes. However, the communication between the IoT systems will face many challenges and increase the cost and risks that lead to the requirement of a cross-platform communication for bridging the ROS-based CPS and other heterogeneous IoT applications.
This paper introduces ROS Edge Node for the interoperability between Robotics domain and other IoT domains, leveraging the highly modular BRAIN-IoT federation, which allows to decentralize, compose and dynamically federate the heterogeneous IoT platforms using OSGi specification, thanks to its dynamic modularity and wide usage in IoT middlewares. Together with the flexible integration with existing IoT devices/platforms within BRAIN-IoT platform, the event-driven asynchronous communication mechanism realizes cross-platform interaction with ROSbased CPS and solves the major challenges faced. This communication mechanism allows dynamic deployment of new functionalities for enhancing/extending the behaviour of robots according to external events. In addition, some specific behaviours to new ”virgin” robots, which might be needed to extend the fleet of robots or replace damaged/low batteries ones can be dynamically deployed at the setup phase. In BRAIN-IoT platform, Edge Node behaves as IoT devices/platform adaptors which integrate the existing IoT devices/platforms. The ROS Edge Node is one type of the Edge Node, which bridges the underlying ROSbased robotics systems and BRAIN-IoT execution environment, thus communicates with various IoT systems connected to the BRAIN-IoT platform. A Service Robotic use case is developed to demonstrate the proposed solution, it shows how the ROS Edge Node enables the fast adaptivity and interoperability between heterogeneous IoT domains in a federated environment.

Risk Assessment in IoT Case Study: Collaborative Robots System

Abstract: Security is one of the crucial challenges in the design and development of IoT applications. This paper presents an approach that focuses on existing security standards to evaluate and analyse the potential risks faced by IoT systems. It begins by identifying system assets and their associated vulnerabilities and threats. A list of security objectives and technical requirements are then defined to mitigate the risks and build a secure and safe system. We use our approach to assess risks in the robotic system for supporting the movement of loads in a warehouse.

Eclipse SAM-IoT 2020 Proceedings

Proceedings of the 1st Eclipse Research International Conference on Security, Artificial Intelligence and Modelling for the next-generation Internet of Things

Virtual Conference | September 17-18, 2020

Co-organized by

  • Eclipse Foundation, Germany
  • LINKS Foundation, Italy
Fog Computing and Blockchain for Massive IoT Deployment

Abstract: The expected exponential growth of IoT devices in future years arises management issues to be resolved. Cloud computing may not be adequate for a massive scale while fog computing brings the ability to manage the distribution of controllability and manageability. Besides, such decentralized architecture is not sufficient to handle sensitive transactions, blockchain-based technology has raised hypes in implementing applications in trust-less environments. This paper proposes a blockchain-based architecture for scalable control of IoT devices. Moreover, smart contracts are developed to facilitate the ledger update process. Experimental results show that the proposed architecture is capable of providing trust on-demand changes with a negligible effect on IoT resources.

Formal Modeling and Verification of Blockchain Consensus Protocol for IoT Systems
  • Authors: Abdelhakim Baouya, Salim Chehida, Saddek Bensalem, and Marius Bozga
  • Location: The 19th International Conference on Intelligent Software Methodologies, Tools and Techniques, Tools and Techniques (SOMET 2020), held in Kitakyushu, JAPAN.
  • eBook: Frontiers in Artificial Intelligence and Applications, Volume 327: Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques

Abstract: Many industrials consider blockchain as a technology breakthrough for cybersecurity, with use cases ranging from cryptocurrency system to smart contracts, and so forth. While IoT systems employ a lightweight communication protocol between physical objects, blockchain may ensure safe information gathering. Unfortunately, the mixture of both technologies has yet to be formally investigated regarding the consensus algorithm. In this paper, statistical model checking is applied to provide quantitative answers on whether the modeled system satisfies safety and liveness properties expressed in LTL temporal logic.

Applied Statistical Model Checking for a Sensor Behavior Analysis

Abstract: The analysis of sensors’ behavior becomes one of the essential challenges due to the growing use of these sensors for making a decision in IoT systems. The paper proposes an approach for a formal specification and analysis of such behavior starting from existing sensor traces. A model that embodies the sensor measurements over the time in the form of stochastic automata is built, then temporal properties are feed to Statistical Model Checker to simulate the learned model and to perform analysis. LTL properties are employed to predict sensors’ readings in time and to check the conformity of sensed data with the sensor traces in order to detect any abnormal behavior.

Exploration of Impactful Countermeasures on IoT Attacks

Abstract:

Risks mitigation in IoT based systems is one of the recent challenges in both academia and industry. In this work, we propose an approach based on the attack-defense tree to assess the relevant countermeasures for protecting IoT infrastructure.

To this end, an attack strategy exploration tool built on the top of the statistical model checker and genetic algorithm is used to select high impactful countermeasures. From that result, defense strategies are highlighted while a compromise guarantee between successful attacks, the cost incurred and the time to perform a sequence of attack actions. We report experiments applied over IoT network attacks.

End-to-end security validation of IoT systems based on digital twins of end-devices
  • Authors : Laurent Maillet-Contoz, Emmanuel Michel, Mario Diaz Nava, Paul-Emmanuel Brun, Kévin Leprêtre, Guillemette Massot
  • Location: Virtual Event – 3rd June 2020 – 2020 Global Internet of Things Summit (GIoTS) – 3rd Workshop on Internet of Things Security and Privacy (WISP)

Abstract:

While the number of digital services is increasing faster and faster, those services rely more and more on IoT systems to collect data and perform data analysis, eventually using AI techniques. In this context, devices are part of the “root of trust” and need to be secured in order to ensure high quality and trusted digital services.

This paper presents an approach to facilitate the integration, verification and then the functional validation of the security into devices based on modeling and simulation. This approach allows reducing the cost impact of adding security layer to physical devices.

BRAIN-IoT: Paving The Way For Next-Generation Internet of Things

Abstract: Nowadays, the adoption of the Internet of Things is drastically increasing in different domains and is contributing to the fast digitalization of several different critical sectors. In the near future, next generation of IoT-based systems will become more complex to be designed and managed. An opportunity for the development of flexible smart IoT-based systems that drive the business decision-making is to take more precise and accurate decisions at the right time, collecting real-time IoT generated data. This involves a set of challenges including the complexity of IoT-based systems and the management of large-scale systems scalability. With respect to these challenges, we propose to automate the management of IoT-based systems mainly based on an autonomic computing approach; these systems should implement cognitive capabilities that allow them learning and generating decisions at the right time. Consequently, we propose a model-driven methodology for designing smart IoT-based systems…

Privacy awareness for IoT platforms: BRAIN-IoT approach
  • Authors: 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”
  • Pages: 24 – 43

Abstract:
With the increasing adaptation of Internet of Things (IoT) platforms in decentralized cloud environments, more focus given towards facilitating the privacy awareness building upon goals set by current European Union (EU) General Data Protection Regulation (GDPR) regulations. Therefore, it is necessary to empower the end users (both private and corporate) of IoT platforms with the capability of deciding which combination of self-hosted or cloud-oriented IoT systems are most suitable to handle the personal data they generate and own as well as with the ability to change the existing (or pre-set) configurations at any time. Furthermore, adaptation of GDPR regulations in IoT platforms is challenging as there are needs for significant efforts to integrate privacy policies in a programmatic way to: (i) increase awareness of users about which data is collected, where it is transmitted, by whom, etc.; (ii) provide controls to enable users to notify such aspects, being at the same time aware of how such a decision affects the quality of the IoT services provided in that IoT platform. BRAIN-IoT project focuses on complex scenarios where actuation and control are cooperatively supported by populations of IoT systems. The breakthrough targeted by BRAIN-IoT is to provide solutions to embed privacy-awareness and privacy control features in IoT solutions. In this work, the authors explore the following key areas: (a) privacy awareness in IoT systems using GDPR regulations and BRAIN-IoT platform, and (b) propose a conceptual framework for Privacy Impact Assessment (PIA) using privacy principles presented in GDPR regulations. The proposed privacy awareness framework is cross-platform, so it is suitable to support a wide number of heterogeneous IoT systems, deployed by corporate and private users.

Integración de Herramientas de Gestión de los Sistemas de Agua Urbana en sistemas IoT Descentralizados
  • Authors: Diego Fernández, Ricardo Váquez, Román Maceiras y Adriel Regueira.
  • Location: JIA 2019 | Línea Temática MD

Abstract:

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.

BRAIN-IoT: Model-Based Framework for Dependable Sensing and Actuation in Intelligent Decentralized IoT System
  • 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)

Abstract:

Modern applications in the Smart Building and Industry 4.0 scenarios will be complex software ecosystems with strict requirements of geographic distribution, heterogeneity, dynamic evolution, security and privacy protection, highly more challenging than the ones required by the current environments. Two of the main challenges arising in the current Internet Of Things scenarios, i.e., the Smart Building one, are, on one side, the requirement of interconnecting several heterogeneous platforms and smart Things in the same environment and, on the other side, the need to be able to evolve the complex software ecosystem deployed, reacting automatically and at runtime to environmental changes, without the human intervention. To address these challenges, BRAIN-IoT establishes a framework and methodology supporting smart cooperative behaviour in fully de-centralized, composable and dynamic federations of heterogeneous Internet of Things platforms. In this way, BRAIN-IoT enables smart autonomous behaviour in Internet of Things scenarios, involving heterogeneous sensors and actuators autonomously cooperating to execute complex, dynamic tasks. Furthermore, BRAIN-IoT enables dynamically deploying and orchestrating distributed applications, allowing the automatic installation and replacement of smart behaviours reacting to environmental changes and User events. Finally, BRAIN-IoT provides a set of components that guarantee the security and privacy protection of the data exchanged using the solution. BRAIN-IoT is a general purpose solution that aims at being adaptable for heterogeneous scenarios, from Service Robotics to Critical Infrastructure Management. This paper introduces a Smart Building use case of the solution, which allows highlighting the advantages given by BRAIN-IoT in such scenario.

Dynamic fog computing platform for event-driven deployment and orchestration of distributed Internet of Things applications

Source: https://ieeexplore.ieee.org/document/8903975

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.

Revisiting the Glue of BIP
  • Author: Jacques Combaz
  • Location: April 2019, MeTRID 2019: 2nd International workshop on Methods and Tools for Rigorous System Design
The modeling language and the associated tools for the analysis
  • Author: Saddek Bensalem
  • Location: February 2019, Dagstuhl-Seminar 1908, “Verification and Synthesis of Human-Robot Interaction”

 

IoT European Security and Privacy Projects: Integration, Architectures and Interoperability
  • 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”
  • Pages 209-221

Abstract:

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.