HOW CAN CAPSTONE PROJECTS IN THE FIELD OF DRIVERLESS CARS CONTRIBUTE TO IMPROVING CYBERSECURITY IN AUTOMATED DRIVING SYSTEMS

Capstone projects undertaken by students in fields related to driverless cars and automated vehicle systems present a significant opportunity to advance cybersecurity in this important and rapidly developing industry. As autonomous vehicles become increasingly connected and rely on various onboard and offboard computing and sensor systems, they become potential targets for malicious attacks that could seriously endanger passengers and other road users if not properly addressed. Through hands-on research and development work, capstone projects allow students to explore vulnerabilities in driverless car systems and propose innovative solutions to strengthen security protections.

Some of the key ways in which capstone projects can help improve autonomous vehicle cybersecurity include identifying new threat vectors, vulnerability testing systems to exposure weaknesses, developing intrusion detection methods, and building more robust access controls and authentication schemes. For example, a group of computer science students may choose to examine how well an autonomous vehicle’s sensors and perception systems stand up to adversarial attacks that aim to fool or compromise the sensors with manipulated input. They could generate synthetic sensor data designed to obscure obstacles or incorrectly identify the vehicle’s surroundings. By testing how the autonomous driving software responds, valuable insights could be gained around weaknesses and new defensive techniques explored.

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Another potential capstone topic is penetration testing the various communication protocols and networks that connect autonomous vehicles and the backend systems that control or assist them. As vehicles become more connected, relying on V2X and cellular connections to infrastructure like traffic control centers, these network layers present expanded surfaces for hackers to infiltrate. Students could attempt to intercept wireless messages between vehicles and infrastructure, inject malicious commands or falsified data, and evaluate how well intrusion is detected and what damage could result. From there, recommendations for stronger authentication, encryption, and intrusion detection across vehicle networks could be proposed.

A third major area capstone projects could address is improving vehicle system and software access controls. As autonomous vehicles will rely on increasingly complex software stacks and vehicle control units running various operating systems and applications, students may choose to audit and penetration test how well these diverse onboard systems are isolated and protected from one another. They could explore techniques for hijacking lower-level mechanism like the vehicle’s CAN bus to gain unauthorized access to safety-critical control software. From such testing, better compartmentalization, access control lists, system integrity monitoring and root cause analysis tools may be designed.

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Additional topics capstone groups could delve into include designing artificial intelligence and machine learning techniques to recognize anomalous or malicious activities in real-time vehicle system telemetry and data feeds. This could help autonomous vehicles gain a self-aware, adaptive sense of security similar to how computer antivirus definitions are regularly updated. Cryptographic protocols and digital signatures ensuring over-the-air software and firmware updates remain unmodified and come from trusted vendors is another prime area. Simulation-based projects examining how well vehicles defend against coordinated multi-vehicle attacks swarming autonomous fleets are yet another relevant approach.

The hands-on, practical nature of capstone projects provides an environment for students to not just theorize about potential security issues but to directly experiment with vehicle and autonomous driving systems. This experience of confronting real challenges during the development process is invaluable for surface weaknesses that may have otherwise gone unnoticed. It allows future security engineers and researchers to gain a deeper, experiential understanding of both vulnerabilities and effective mitigation approaches within these complex, safety-critical systems. The testing and solutions developed through capstone work can then be published or shared with developers to immediately strengthen protections as the driverless industry continues to evolve rapidly. Capstone research makes a key contribution to improving the cyber-resilience of autonomous vehicles through an active, student-led process of identify-test-solve within a controlled, supervised environment.

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As automated driving systems take to our roads in coming years, cybersecurity must be a top priority to ensure public safety. Capstone projects allow students to play an active role in surveying the cybersecurity landscape within this emerging field and devising innovative solutions through hands-on practical research and development. The testing performed identifies weaknesses while the solutions proposed help secure these advanced systems from the earliest stages of development. Capstone work is thus an impactful method for enhancing cyber protections for driverless vehicles and mitigating threats to promote responsible, safe innovation within this important new mobility revolution.

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