Overview What You Will Learn Curriculum Instructor

Course Overview

Cybersecurity for robotics is a multidisciplinary research domain growing in relevance and importance due to the continuous growth of robotics systems and the increase in cybersecurity, safety risks, and challenges. Threats can penetrate all the way to the shop floor where the production takes place, affecting the consumers. Safety standards demand a security mechanism that protects the robot endpoints and fulfills all the security requirements, a Robot Endpoint Protection Platform (REPP). Self-driving cars could be hacked with ransomware, not allowing owners to enter, start or exit the vehicle until a ransom is paid. Terrorist hackers could disable networks, range sensors, and cameras, resulting in multiple collisions. An autonomous vehicle’s operating system could be hacked, exposing personal information on other connected devices. Hacked vehicles could potentially be rerouted to an area where a robbery or assault is planned.  

The course begins with an introduction to robotics and autonomous systems. As you move on, you will learn to model robot cybersecurity threats. Further, you will explore modelling risk and characterization of the robotic system. Next, you will learn modelling safety issues and authentication techniques. After that, you will discover cloud robotics and security, including cyber-physical systems.  Furthermore, you will learn mobile robotics and its security. Next, you will discover how to simulate the network and implement security in development.  

By the end of the course, you will gain expertise in robotics, cyber-security, verification and validation, control theory, artificial intelligence, unmanned systems, machine learning, formal methods, and human-robot interaction.  

What You Will Learn

  • Learn the evolution of cybersecurity for robotics and autonomous systems and the challenges.
  • Explore Industrial Robotics
  • Get acquainted with collaborative robots
  • Autonomous mobile robots (AMRs)
  • and Autonomous Systems.
  • Hands-on cybersecurity
  • National Institute of Standard and Technology (NIST) framework
  • types of cyber-attacks
  • security vulnerabilities
  • Impact of Artificial Intelligence (AI) and Machine Learning (ML) in Cybersecurity.
  • Learn to resolve Cyber Issues
  • Security Architectures
  • and Robot Operating System (ROS) Vulnerabilities.
  • Enhance Security of Networked Robotic Systems.

Program Curriculum

  • Fundamentals
  • High-level Overview
  • Understanding Cybersecurity
  • Understanding Robotics and Autonomous Systems
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Evolution of the Internet of Things (IoT)
  • Industrial Internet of Things (IIoT)
  • Robotic Process Automation (RPA)
  • Chapter 2 Quiz

  • Cybersecurity Issues in Robotics
  • Cyber-physical Systems (CPS) and Robotic Systems
  • Robot Security Framework
  • Confidentiality, Integrity, & Availability - CIA Triad
  • Chapter 3 Quiz

  • DoS & DDoS Attacks
  • Spoofing
  • Man-in-the-Middle Attack (MITM)
  • Remote Access Trojan (RAT) Attack
  • Various Other Cyber-attacks
  • Chapter 4 Quiz

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Deep Learning (DL)
  • Open-source Software Collaboration
  • Open-source Initiatives for AI, ML, and DL
  • Chapter 5 Quiz

  • Healthcare
  • Retail
  • Automotive
  • Public Safety and Public Transport
  • Financial Services
  • Campus Network
  • Manufacturing
  • Oil and Gas
  • Smart Facilities
  • Logistics

  • Healthcare
  • Retail
  • Automotive
  • Public Safety and Public Transport
  • Financial Services
  • Campus Network
  • Manufacturing
  • Oil and Gas
  • Smart Facilities
  • Logistics

  • Security Practices and Designs
  • Solutions to Secure Robotics Ecosystem
  • Latest Technologies and Strategies to Address Vulnerabilities
  • Technology Labs and Incubators
  • Setting Expectations and Establishing Alignment
  • Industry Research Tools and Resources of Robotics and Autonomous Systems

  • Ethical Use of Robotics and Autonomous System
  • Ethical Use of Artificial Intelligence (AI)
  • Ethical Use of Machine Learning (ML)
  • Ethical Use of Autonomous Systems
  • Use of Robotics & Autonomous Systems in Long-term Care
  • Technological Risks and Ethical Issues
  • Legal and Other Issues

Overview of Key Takeaways from Course

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Instructor

Jyothsna R Kasu

Jyothsna Kasu has over 20 years of progressive, enriching experience across Consulting, IT/ITES, Manufacturing, and Electronics industry verticals. She is a dual specialization in IT & Systems. She is certified in Big Data Analytics (Hadoop ecosystem), Data Science, Robotics, Cyber Security, AI & Coding, and Various Analytics Platforms. She has CEHCertified Ethical Hacker from EC-Council. She is also the author of the books “The Art of Being Invisible” and “Digital Disruption” which are on cybersecurity and new digital technologies.

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