AI and machine learning are revolutionising digital health—but without the right safeguards, they can quickly become a liability. The solution? ISO 27001.
Artificial intelligence (AI) and machine learning are game changers—but they also come with risks. If not properly secured, these powerful tools can become targets for hackers, data theft, or even malicious attacks that feed them false information. Such breaches can lead to serious issues like data loss, legal troubles, financial setbacks, and damage to your company’s reputation.
One effective way to protect your AI systems is by following ISO 27001—the international standard for managing information security. This guide explains how ISO 27001 can help you secure your AI and machine learning environments.
AI systems face several threats that can compromise the confidentiality, integrity, or availability of your data. Here are some common risks:
ISO 27001 provides a clear framework to manage information security risks through well-defined policies and procedures. Here’s how you can apply it to secure your AI and machine learning systems:
Inventory of Assets (A.5.9):
Keep a detailed list of all your AI systems and related assets. Knowing exactly what you have is the first step to protecting it.
Information Classification (A.5.12):
Categorise your data based on its sensitivity. This helps in deciding what level of protection each type of data needs.
Secure Data Transfer (A.5.14):
Use encryption and secure protocols when transferring data to ensure it isn’t intercepted.
Access Control (A.5.15):
Limit access to your AI systems and data so that only authorised personnel can make changes or retrieve information.
Supplier Security (A.5.19):
Verify that any external partners or service providers follow your security guidelines to keep your AI environment safe.
Legal and Regulatory Compliance (A.5.31):
Identify and meet all legal and contractual obligations related to the use of AI and machine learning technology.
Secure Development Life Cycle (A.8.25):
Incorporate security checks at every stage of your AI system’s development to prevent vulnerabilities from being built into your products.
Here’s a step-by-step plan to integrate ISO 27001 practices into your AI security strategy:
Develop a Security Policy:
Create a clear policy that outlines how to protect your AI and machine learning systems. Include guidelines for access, data handling, and response procedures in case of a breach.
Maintain an Asset Inventory:
Keep an updated list of all your AI systems and the data they use. This helps in monitoring and securing your assets.
Classify Your Data:
Identify which data is most sensitive and ensure it receives additional protection.
Secure Data Transfers:
Always use encrypted channels and secure methods when moving data between systems.
Enforce Access Controls:
Limit system access to trusted, authorised personnel only.
Collaborate with Trusted Suppliers:
Make sure any third-party providers adhere to your security standards.
Stay Compliant:
Regularly review and update your practices to ensure they meet all legal and regulatory requirements.
Embed Security in Development:
Incorporate security measures at every phase of your AI system’s development process.
By following these steps, you not only protect your data but also build a secure, reliable foundation for your AI initiatives. This proactive approach can help you avoid costly breaches, build customer trust, and maintain a competitive edge in an increasingly digital world.
If you have any more questions or would like more insights on AI security guidance, consider scheduling a strategy call with our team.