The National Cybersecurity Centre (NCSC) and the US Cybersecurity and Infrastructure Security Agency (CISA) and other international organizations recently jointly released a new guide on the security of artificial intelligence systems. This guide is designed to provide comprehensive security guidance to developers around the world to ensure that security is always at the heart of designing, developing, deploying and operating AI systems. The guide was recognized and signed by 21 agencies and ministries from 18 countries, marking an important step in global cooperation in the field of AI security.
This guide covers all key stages of the AI system life cycle, including security design, security development, security deployment and security operation and maintenance. Through systematic guidance, it helps developers identify potential security risks in each link and take appropriate protective measures. Whether it is a large enterprise or a startup, it can benefit from it, ensuring that its AI systems remain robust in complex and changing network environments.
The guide has a wide range of applications, not only for all types of AI systems, such as machine learning models, deep learning frameworks and automated decision-making systems, but also for professionals working in artificial intelligence, including data scientists, engineers and project managers. By providing standardized security practices, this guide sets a new security benchmark for the global AI industry.
During the security design phase, the guide emphasizes the concept of "security first", and recommends that developers consider potential security threats early in the system design and take preventive measures. For example, through data encryption, access control, and authentication, the core components of the system are protected from attacks. In addition, the guide also recommends developers to adopt a modular design so that they can be quickly isolated and repaired when security issues arise.
During the security development phase, the guide proposes best practices such as code review, vulnerability scanning, and continuous integration. The development team should conduct security audits on the code regularly to ensure there are no hidden vulnerabilities or backdoors. At the same time, the guide also recommends continuous monitoring using automation tools to promptly detect and fix security issues during development.
During the security deployment phase, the guide emphasizes the importance of environment configuration and permission management. Developers should ensure that the AI system is in a secure environment when deployed and strictly control access rights to prevent unauthorized users from operating on the system. In addition, the guide also recommends comprehensive security testing before deployment to ensure that the system does not experience unexpected problems during actual operation.
During the safety operation and maintenance phase, the guideline proposes strategies for continuous monitoring and emergency response. The development team should establish a complete monitoring mechanism to track the operating status of the system in real time and take action quickly when abnormalities are found. At the same time, the guide also recommends a detailed emergency response plan so that the system can be quickly restored to normal operation in the event of a security incident.
The release of this guide not only provides authoritative guidance for the security development of AI systems, but also lays an important foundation for security governance in the global AI industry. With the rapid development of AI technology and the increasing security issues, the introduction of this guide undoubtedly provides valuable reference for the industry. In the future, with the joining of more countries and institutions, global AI security cooperation will be further strengthened to safeguard the healthy development of AI technology.