Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems image

Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

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ABOUT THE BOOK

This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

TABLE OF CONTENTS

    1. Reliable Real-Time Message Scheduling in Automotive Cyber-Physical Systems

      • Vipin Kumar Kukkala, Thomas Bradley, Sudeep Pasricha
      Pages 3-42

    2. Evolvement of Scheduling Theories for Autonomous Vehicles

      • Wanli Chang, Nan Chen, Shuai Zhao, Xiaotian Dai
      Pages 43-80

    3. Distributed Coordination and Centralized Scheduling for Automobiles at Intersections

      • Yi-Ting Lin, Chung-Wei Lin, Iris Hui-Ru Jiang, Changliu Liu
      Pages 81-117

  2. Security-Aware Design

    1. Front Matter

      Pages 119-119
      PDF

    2. Security-Aware Design of Time-Critical Automotive Cyber-Physical Systems

      • Vipin Kumar Kukkala, Thomas Bradley, Sudeep Pasricha
      Pages 121-153

    4. Resource Aware Synthesis of Automotive Security Primitives

      • Soumyajit Dey, Ipsita Koley, Sunandan Adhikary
      Pages 189-224

    5. Gradient-Free Adversarial Attacks on 3D Point Clouds from LiDAR Sensors

      • Jan Urfei, Fedor Smirnov, Andreas Weichslgartner, Stefan Wildermann
      Pages 225-256

    6. Internet of Vehicles: Security and Research Roadmap

      • Arunmozhi Manimuthu, Tu Ngo, Anupam Chattopadhyay
      Pages 257-287

  3. Intrusion Detection Systems

    1. Front Matter

      Pages 289-289
      PDF

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

      • Vipin Kumar Kukkala, Sooryaa Vignesh Thiruloga, Sudeep Pasricha
      Pages 317-347

    4. Stacked LSTM Based Anomaly Detection in Time-Critical Automotive Networks

      • Vipin Kumar Kukkala, Sooryaa Vignesh Thiruloga, Sudeep Pasricha
      Pages 349-380

    5. Deep AI for Anomaly Detection in Automotive Cyber-Physical Systems

      • Sooryaa Vignesh Thiruloga, Vipin Kumar Kukkala, Sudeep Pasricha
      Pages 381-397

    6. Physical Layer Intrusion Detection and Localization on CAN Bus

      • Pal-Stefan Murvay, Adriana Berdich, Bogdan Groza
      Pages 399-423

    9. Machine Learning for Security Resiliency in Connected Vehicle Applications

      • Srivalli Boddupalli, Richard Owoputi, Chengwei Duan, Tashfique Choudhury, Sandip Ray
      Pages 485-505

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