Author: i2cat

CARAMEL at the IoT Solutions World Congress

CARAMEL at the IoT Solutions World Congress

The CARAMEL project had a successful participation in the activities of the IoTS WC, thanks to the participation of more than 400 people who were interested in the project and who were offered a personalised explanation through the official project tours or the individual conversation, to inform them about the most outstanding results of the project.

We are grateful for the participation of all the members of the consortium who prepared the videos shown during the days of the congress. We highlight the participation of I2Cat, Capgemini, Panasonic, Atos and Nextium who had the opportunity to be in the testbed offering specific information about the project to each of the visitors to the CARAMEL testbed.

It is relevant to mention that thanks to the participation in this event we were able to establish communication with several cybersecurity organisations through which we will look for future collaboration opportunities.

We appreciate the participation of each visitor because without their visit the CARAMEL testbed demonstration would not have been the same.

We invite you to follow the official project channels where we share the latest news and upcoming events of the project.

H2020 Caramel Project (@caramel_project) / Twitter

https://www.linkedin.com/company/13066014

21st GA meeting

21st GA meeting

Today is being held the CARAMELs 21st general assembly among all members of the consortium. After some months of reluctance to have these live conversations, it is the first face-to-face meeting.

The meeting takes place on the premises of the University of Cyprus, in the library. (Learning Resource Centre – Library “Stelios Ioannou”) Aglantzia, Nicosia.

In this meeting, the project focuses on organising the activities necessary to carry out the final demonstrations of the project, i.e. the participation of the IoTS WC as well as during the final evaluation.

It is also planned to synchronise the activities carried out during the duration of the project so that they are completed on time.

One of the objectives of CARAMEL focuses on designing and implementing detection and response techniques based on artificial intelligence and multimodal fusion of sensors available on autonomous vehicles to mitigate attacks on autonomous vehicles.

CARAMEL at the DATE2022

CARAMEL at the DATE2022

The DATE2022 conference is intended as a meeting point for researchers, software and hardware designers, manufacturers of electronic circuitry, among others, to focus on technology and systems.

During this event the CARAMEL project participated in the discussion session dedicated to providing a platform for discussion of opportunities and collaborations for innovation and research in Europe, in which the project’s technical coordinator Peter Hofmann took part in the panel session “The Good, the Bad and the Trendy of Multi-Partner Research Projects in Europe“.

Although the conference initially had to be held face-to-face, it had to be reorganized in the short term towards an online format.

  • What makes the project concept unique?
    In the CARAMEL project, we strive to implement machine-learning based detection of attacks against the connected and/or autonomous vehicle by analysing sensor data, V2X data, and the status of embedded controllers like the OBU (on-board unit) in real-time using a tamper-proof device that directly integrated into the car – the anti-hacking device (AHD). This architecture and concept are novel and innovative, and CARAMEL is the first project to implement and demonstrate this.
  • What project outcomes can be of use to the DATE 2022 community?
    Even as CARAMEL implements its concepts and architectures in the automotive space, the key CARAMEL innovations are transferable to other IoT and Embedded applications domains as well, such as factory floors, building automation systems or others. Therefore, the CARAMEL presentation and presence of CARAMEL representatives during the conference would be of value to the DATE 2022 community.
  • What inputs (solutions) are expected from the DATE 2022 community?
    In the CARAMEL project, several integration options for the anti-hacking device based on different IoT devices have been pursued already. However, for the concept to be commercially viable and cost-effective, the concept of a machine-learning-based intrusion device must be even better integrated into commercial offerings for the Automotive and IoT market. The DATE 2022 community could provide valuable input for that endeavour.
  • What new research topics and trends does the project introduce?
    CCAM and IoT both will face important security challenges in the future as bad actors discover these new areas for their activities. Since bad actors will use machine learning to subvert machine-learning-based processes and algorithms in the CCAM and IoT world (eg. using Generative Adversarial Networks (GAN)), a trend in the security industry is also to use machine learning to detect and counter these attacks. The CARAMEL project showcases this approach in the Automotive context.
  • Technical Meeting

    Technical Meeting




    Today, the CARAMEL consortium started a technical meeting among all participants to synchronise the activities carried out to achieve the proposed goals and present the challenges related to the integration of the various research tasks carried out over the last months.
     
    We can recall that one of the objectives of CARAMEL focuses on designing and implementing detection and response techniques based on artificial intelligence and multimodal fusion of the sensors available in autonomous vehicles. In addition, to obtain a deep learning technique that can be used in anticipation of cyber-attacks that intend to perform malicious activities on the autonomous vehicle.
     
    The meeting was opened by Petros Kapsalas, who updated the activities carried out as part of Work Package #6.
     
    Thus, the advantages of artificial intelligence as a mitigation technique to counter elaborate attacks were mentioned.
    Later, the consortium members were reminded about the used vehicle to demonstrate the project’s outcomes in the final review.
     
    Afterwards, each consortium member involved in activities related to pillar 1: Autonomous Mobility, presented their progress to synchronise efforts in a timely manner.
    CARAMEL 2nd OEM & Partner Workshop

    CARAMEL 2nd OEM & Partner Workshop

    The CARAMEL project will held the second OEM and Partners workshop on 16 November 2021, from 14:00 to 17:00. This workshop aims to present the most outstanding results of the research and development carried out by the different members of the consortium. Furthermore, this workshop is also oriented to OEM representatives, which could increase the visibility of the project and collect opinions on the topics addressed by CARAMEL.

    The objective of this workshop will be to highlight the achieved results toward the development of Artificial Intelligence-based cybersecurity for connected and automated vehicles.

    The CARAMEL project bases its research on 4 fundamental pillars for the safety of connected autonomous vehicles.

    Main Pillars of the project:

    Pillar 1: Autonomous Mobility
    Pillar 2: Connected mobility
    Pillar 3: Electromobility
    Pillar 4: Remote Control Vehicle (RCV)

    Autonomous Mobility

    • Taxonomy of the attacks.
    • Cyber attacks Detection and Mitigation on Sensing and Navigation modalities.
    • Elevation of Perception Engines as core modules for cyber-attack detection  & mitigation engines.
      • Towards robustifying D-CNNs to tackle adversarial attacks on the scene layer.
    • Multimodality and Redundancy of Sensors beat malicious attacks on CAVs.
    • Fall back actions to enhance safety.
    • Key Performance Indicators for assessing Mitigation Performance.

    Connected mobility

    • Interoperability between radio technologies for V2X communications
    • Secure V2X communications and related hardware
    • GNSS, V2X and HW attack detection and response process
    • Vehicle tracking using its signature certificates

    Electromobility

    • Communication architecture of an EV charging network

    Remote Control Vehicle (RCV)

    • ML-based traffic between 5G-RCV 
    • Control Center anomaly detection
    • prediction algorithm development

    Don’t miss this excellent opportunity to learn more about the activities carried out to develop cybersecurity based on artificial intelligence for autonomous and connected vehicles.

    CARAMEL at MMSP 2021

    CARAMEL at MMSP 2021

    The IEEE 23rd International Workshop on Multimedia Signal Processing, organised by the IEEE Signal Processing Society, Centre for Immersive Visual Technologies and Tampere University, will be held from 6th-8th October in Tampere, Finland.

    The congress will be the meeting point for professionals from academia and industry developing or are carrying out projects in the field of multimedia signal processing, aiming to share knowledge, exchange ideas and explore future research directions.

    The IEEE MMSP 2021 is a hybrid event. This includes the face-to-face gathering at Scandic Hotel Rosendahl and online engagement through a virtual platform.

    This event will include the presence of the University of Patras members of the CARAMEL consortium, who will be presenting the paper:

    Deep multi-modal data analysis and fusion for robust scene understanding in CAVs

    Deep learning (DL) tends to be the integral part of Autonomous Vehicles (AVs). Therefore the development of scene analysis modules that are robust to various vulnerabilities such as adversarial inputs or cyber-attacks is becoming an imperative need for the future AV perception systems. In this paper, we deal with this issue by exploring the recent progress in Artificial Intelligence (AI) and Machine Learning (ML) to provide holistic situational awareness and eliminate the effect of the previous attacks on the scene analysis modules. We propose novel multi-modal approaches against which achieve robustness to adversarial attacks, by appropriately modifying the analysis Neural networks and by utilizing late fusion methods. More specifically, we propose a holistic approach by adding new layers to a 2D segmentation DL odel enhancing its robustness to adversarial noise. Then, a novel late fusion technique has been applied, by extracting direct features from the 3D space and project them into the 2D segmented space for identifying inconsistencies. Extensive evaluation studies using the KITTI odometry dataset provide promising performance results under various types of noise.

    7th October 2021

    The IEEE 23rd International Workshop on Multimedia Signal Processing

    CARAMEL at AIBIGDATA21

    CARAMEL at AIBIGDATA21

    The AI & Big Data Congress 2021, organised by the Innovation Centre for Data Tech and Artificial Intelligence, will be held on 15th September at the AXA Auditorium in Barcelona.

    The congress will be the meeting point for professionals, suppliers, and companies developing or are carrying out projects in the field of AI & Big Data.  

    This edition will talk about the new Artificial Intelligence challenges, market trends and best practices of pioneer companies, technological innovations and their applications; and success stories explained in detail. 

    Don’t miss the opportunity to participate in this event in which Jordi Guijarro (CARAMEL’s Project coordinator) will present a session of the proof of concept envisioned by the CARAMEL project.

    H2020 CARAMEL: AI-based cybersecurity for connected and automated vehicles

    15th September 2021

    Registration link

    7th edition AI & Big Data Congress | 14-15 September 2021 (aicongress.barcelona)

    Automotive Threat Modelling Tutorial

    Automotive Threat Modelling Tutorial

    CARAMEL aims to produce a cybersecurity system based on artificial intelligence to combat cyber threats present in autonomous vehicles.

    However, have you ever wondered how to perform a detailed analysis to identify threats in autonomous vehicles?

    CARAMEL’s members created a tutorial that explains how to develop and analyse an automotive threat model using Microsoft’s Threat Modelling tool through the STRIDE technique.

    Threats
    Spoofing
    Tampering
    Repudiation
    Information disclosure
    Denial of service
    Elevation of privilege

    The STRIDE technique tries to identify as many possible threats in the system by decomposing a more extensive system into its most relevant components.


    The STRIDE technique was named after the threats, it can identify.

    We invite you to register and download the tutorial at the following link.

    References

    Uncover Security Design Flaws Using The STRIDE Approach | Microsoft Docs

    CARAMEL demo video series

    CARAMEL demo video series

    As part of the project’s dissemination activities, we have opted to share video demonstrations of some of CARAMEL’s developments.

    Each of the videos is composed of an introduction to the developed system, followed by a general explanation of the system, and finally a presentation of the most outstanding results of the particular system.

    Within the scope of the developments presented, you can find systems developed for some of the pillars addressed by Caramel such as:

    Pillar 1: Autonomous vehicles
    Pillar 2: Connected vehicles

    The titles of the videos are

    Title
    RSU-OBU-TestBed
    Traffic sign anomaly detection and mitigation pipeline
    Detecting possible attacks on the camera sensor using a deep learning approach
    In-vehicle Location Spoofing Attack Detection
    Holistic Situational Awareness with ML Application
    Collaborating mitigation mechanism against GPS spoofing

    The videos can be found at the following link or through the following video gallery

    CARAMEL Workshop

    CARAMEL Workshop

    As part of the CARAMEL activities on 27 May 2021, starting at 09:00, a 2-hour virtual workshop will be held. The CARAMEL project will introduce their activities to representatives of OEMs to increase the reach and gather opinions about the topics addressed by CARAMEL.

    The objective of this workshop will be to highlight the achieved results toward the development of Artificial Intelligence-based cybersecurity for connected and automated vehicles.

    Main Pillars of the project

    Pillar 1: Autonomous Mobility
    Pillar 2: Connected mobility
    Pillar 3: Electromobility
    Pillar 4: Remote Control Vehicle (RCV)

    Registration Link

    https://us02web.zoom.us/meeting/register/tZcrd-qoqjMvHNLMw6lN3bhzAkkMwaMXky1U

    Theme: Elation by Kaira.