7 Automotive Cybersecurity Best Practices 

5. Ensure Up-to-date Cryptographic Algorithms

Stay ahead of cybercriminals by using the latest cryptographic algorithms to protect sensitive data and communications. Using up-to-date cryptographic algorithms is crucial for ensuring the security of communications between vehicles and other systems.

NVIDIA, for example, uses AI-powered data processors and chips to operate and protect self-driving cars. Their software and cloud-based technologies help autonomous vehicles securely learn and relay driving data. 

Many leading car manufacturers, like Tesla, Mercedes-Benz, Audi, Toyota, and Volkswagen, rely on NVIDIA's deep learning systems to enable and secure their self-driving vehicles.

6. Build a Framework for Governance

When developing a governance framework, consider defining and communicating the overall scope, mission, and vision. A strong governance framework ensures your organization's commitment to cybersecurity. 

Key elements include:

• Defining Scope: Clearly defining the mission, vision, and overall scope of your cybersecurity strategy.

• Identifying Functions: Identifying key functions and roles in your organization.

• Organizing Leadership: Determining how and where decision-making occurs.

• Stakeholder Engagement: Strategies for engaging stakeholders across the board.

• Policy and Process Development: Developing and maintaining robust policies and processes.

• Performance Management: Defining relevant metrics to measure performance.

7. Implement Security Development Lifecycle (SDL)

Integrating security into the development lifecycle is essential.

The Security Development Lifecycle (SDL) is a process that developers use to build more secure software by addressing security compliance requirements during the development process. It involves the following steps:

• Training: All employees, especially developers and engineers, should receive security awareness training appropriate to their role. This includes general security awareness training for new hires and annual refresher training for all employees.

• Requirements: Define clear security and privacy requirements at the start of the project. These requirements should be based on factors like the type of data the product will handle, known threats, best practices, regulations and industry requirements, and lessons learned from previous incidents.

• Design: Once the requirements have been defined, begin designing the automotive system. As part of this process, create threat models to help identify, categorize, and rate potential threats according to risk.

• Implementation: Write the code that implements the design. During this phase, ensure that all security and privacy requirements are properly addressed.

• Verification: Each phase of the SDL should contain mandatory checks and approvals to ensure all security and privacy requirements and best practices are properly addressed.

• Release: Once the system has been thoroughly tested and verified, it can be released to customers.

• Response: Conduct activities after the core phases to ensure that the system remains secure after deployment. This includes monitoring for new threats and vulnerabilities and responding appropriately when they are detected.

• Maintenance: Continuously support the application after its deployment. This includes regularly updating the system to address new threats and vulnerabilities, as well as making improvements based on user feedback and changing business needs.

Remember that SDL is a continuous process, meaning that security and privacy requirements change throughout the product’s lifecycle to reflect changes in functionality and the threat landscape.