Imagine a calm morning commute in your shiny new autonomous car. You’re sipping coffee, catching up on emails, and leaving the “driving” to the AI. Then, suddenly, your car takes a sharp, unexpected turn. No, it’s not a glitch—it’s a hacker, and they’re now in the driver’s seat. 

Sounds like a scene from a sci-fi thriller, right? But the truth is, autonomous vehicles (AVs) are not just transforming transportation—they’re also opening new doors for cybercriminals. As our cars become smarter and more connected, they’re becoming attractive targets for hackers with malicious intent.  

Threats to Autonomous Vehicles 

1. Remote Hijacking  

In 2015, Charlie Miller and Chris Valasek famously hacked a Jeep Cherokee from miles away. Using nothing but a laptop, they controlled its steering, brakes, and even the transmission. Imagine being on a highway and realizing your car is no longer yours to control. This isn’t just theoretical—it’s a reality that sent shockwaves through the automotive industry. (Source: https://www.bbc.com/news/technology-33650491) 

2. GPS Spoofing 

In 2020, researchers demonstrated how they could trick a Tesla’s autopilot by subtly altering GPS signals. The car believed it was on a different road and attempted to adjust its course accordingly. What if this were done on a busy highway or near a cliff? The potential for disaster is immense. 

3. Data Breaches 

Your autonomous car isn’t just a vehicle; it’s a moving data center. From your driving habits to your favourite destinations, you connect your entire device, it stores a wealth of personal information. In 2021, a hacker breached a major automaker’s system and accessed sensitive customer data, proving that cars are just as vulnerable as laptops and smartphones. 

4. Communication Interception  

AVs rely heavily on Vehicle-to-Everything (V2X) communication to talk to traffic lights, other vehicles, and even pedestrians. Hackers could intercept these communications, sending fake signals to cause accidents or create gridlock. In a 2016 experiment, Israeli researchers hacked smart traffic lights, showing how easy it could be to bring a city to a standstill. 

5. Ransomware Attacks  

Picture this: You’re late for an important meeting, and your car refuses to start. A message flashes on the dashboard demanding cryptocurrency to unlock your vehicle. This isn’t far-fetched. Ransomware attacks on connected devices are rising, and cars could be next. 

Key Measures to Safeguard Autonomous Vehicles 

1. Encrypted Communication: Secure all V2X communications with strong encryption protocols like TLS 1.3. 

2. Resilient Software Updates: Use authenticated, secure OTA updates to prevent malicious modifications. 

3. Endpoint Security: Integrate secure boot and anti-malware protections for critical vehicle systems. 

4. Intrusion Detection: Deploy AI-driven IDPS for detecting and mitigating abnormal network behaviour. 

5. Sensor Reliability: Employ redundant systems to cross-verify sensor data and prevent spoofing. 

6. Access Control: Enforce strict RBAC and encrypt sensitive data both in transit and storage. 

7. Resilience Engineering: Design fail-safe mechanisms for uninterrupted safe operation during attacks. 

8. Standard Compliance: Adhere to ISO/SAE 21434 and UNECE WP.29 for cybersecurity governance. 

9. Supply Chain Security: Audit third-party components to ensure cybersecurity compliance. 
   
   
10. Continuous Monitoring: Analyse telemetry and update threat intelligence to counter new risks.

Technologies Advancing Autonomous Vehicles 

1. Artificial Intelligence (AI) and Machine Learning: These are foundational for improving perception, decision-making, and prediction in AV systems. They enable vehicles to handle complex scenarios like inclement weather or high-speed urban driving. 

2. Lidar and Sensor Fusion: Lidar (light detection and ranging) remains critical for creating detailed 3D maps, while combining data from cameras, radar, and lidar enhances situational awareness. Innovations aim to reduce costs while maintaining high precision. 

3. Edge Case Management: Developers are focusing on edge cases—rare or unusual scenarios—through robust simulation tools and real-world data to refine AV decision-making capabilities. 

4. High-Performance Computing: Autonomous systems require powerful chips and hardware accelerators to process vast data in real-time. Cost reductions are expected by the early 2030s as these technologies become commoditized. 

5. 5G Connectivity: Ultra-fast communication networks are crucial for vehicle-to-everything (V2X) communication, enabling vehicles to interact with infrastructure, other vehicles, and pedestrians seamlessly. 
   
   
6. Over-the-Air (OTA) Software Updates: Continuous updates allow manufacturers to improve AV features, enhance security, and address bugs without physical interventions.  

Emerging Trends and Use Cases 

• Robotaxis and Roboshuttles: Cities are already testing limited-scale robotaxi services, with larger rollouts anticipated around 2026. These are likely to start in controlled environments or favorable weather regions. 
• Autonomous Freight: Autonomous trucking is a promising early use case, particularly for highway freight routes. Tests are ongoing in regions with favorable regulations and weather. 
• Closed Environments: Ports, logistics hubs, and mining operations are adopting autonomous vehicles for specific, controlled use cases. 

Autonomous vehicles promise a safer, smarter future, but they also come with risks that can’t be ignored. Hackers are evolving as quickly as the technology they target, and the automotive industry must stay one step ahead. 

By learning from past incidents, adopting best practices, and preparing for future challenges, we can ensure that self-driving cars don’t just transform how we travel—they also keep us safe along the way. Because in the end, the only one who should be in the driver’s seat is you.

Written By
Bhairavi Joshi
Head of Marketing, CyberFrat