Robot Operating System (ROS) is becoming more and more important and is used widely by developers and researchers in various domains. One of the most important fields where it is being used is the self-driving cars industry. However, this framework is far from being totally secure, and the existing security breaches do not have robust solutions. In this paper we focus on the camera vulnerabilities, as it is often the most important source for the environment discovery and the decision-making process. We propose an unsupervised anomaly detection tool for detecting suspicious frames incoming from camera flows. Our solution is based on spatio-temporal autoencoders used to truthfully reconstruct the camera frames and detect abnormal ones by measuring the difference with the input. We test our approach on a real-word dataset, i.e. flows coming from embedded cameras of self-driving cars. Our solution outperforms the existing works on different scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Intrusion detection on robot cameras using spatio-temporal autoencoders: A self-driving car application


    Beteiligte:
    Amrouche, Faouzi (Autor:in) / Lagraa, Sofiane (Autor:in) / Frank, Raphael (Autor:in) / State, Radu (Autor:in)


    Erscheinungsdatum :

    01.05.2020


    Format / Umfang :

    358933 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Intrusion Detection By Linear Active Cameras

    Deparis, J. P. / Duvieubourg, L. / Postaire, J. G. et al. | British Library Conference Proceedings | 1996


    Intrusion Detection and Tracking with Pan-Tilt Cameras

    Biswas, A. / Guha, P. / Mukerjee, A. et al. | British Library Conference Proceedings | 2006


    Real-Time Intrusion Detection in Automotive Cyber-Physical Systems with Recurrent Autoencoders

    Kukkala, Vipin Kumar / Thiruloga, Sooryaa Vignesh / Pasricha, Sudeep | Springer Verlag | 2023


    3D Intrusion Detection System with Uncalibrated Multiple Cameras

    Kawabata, Satoshi / Hiura, Shinsaku / Sato, Kosuke | Springer Verlag | 2007


    Maneuver-based Trajectory Prediction for Self-driving Cars Using Spatio-temporal Convolutional Networks

    Mersch, Benedikt / Höllen, Thomas / Zhao, Kun et al. | ArXiv | 2021

    Freier Zugriff