On 23 February 2024 the Ministry of Industry and Information Technology issued the Industrial Data Security Capability Enhancement Implementation Plan (2024-2026) as MIIT Wang’an [2024] No. 34. The document addresses industrial data classification, identification of important data, security assessment, monitoring and early warning, incident response and capability building.
It is not a statement of principles. It breaks “capability” into checkable actions. For industrial companies and the AI suppliers serving them, it amounts to a three-year construction plan.
Capability broken into checkable actions
Classification is not a one-off register but a process updated as the business changes. Identification of important data requires both sector catalogues and the company’s actual situation. Security assessment, monitoring and incident response correspond to routine operating mechanisms rather than post-incident remediation. Because the plan links these steps, inspections will look at policies, records and technical measures.
All three are needed. A policy states who is responsible, records show that work was done, and technical measures keep it running. A policy without records is hard to sustain in an assessment.
Important data catalogue and filing
Identification of important data in industry usually follows catalogues issued by sectors and localities. Companies must decide whether their data falls within scope and complete catalogue reporting or filing as required. Whether process optimisation data or equipment operating data generated by an AI project constitutes important data requires sector-specific analysis; it cannot be treated as ordinary trade secrets by default.
Treating important data as ordinary trade secrets creates a gap, because the two regimes do not overlap. Trade secret protection focuses on confidentiality and access control; important data also triggers security assessment, outbound transfer and incident reporting.
Assessment and monitoring
Security assessment examines the risks of processing activities, including collection, storage, use, processing, transmission, provision and disclosure. Monitoring requires the ability to detect abnormal access, bulk export and attacks. Both depend on logs and audit foundations; without them, assessment conclusions lack support.
Assessment is not a one-time acceptance. When the business, systems or data flows change, earlier conclusions may no longer hold. Companies need trigger rules stating when reassessment is required.
The harder part of monitoring comes after an alert. Detecting abnormal access is only the first step. Locating the account, terminating the session, preserving evidence and reporting as required determine whether the mechanism works. Many companies buy monitoring tools without a duty roster and escalation procedure.
Supply chain and cross-border allocation
When an industrial company engages an AI supplier, the common models are on-site deployment or inference through an API. Who controls the data, who can access it and whether it leaves the country determine how responsibility is allocated. Contracts should state purpose, duration, security measures, incident notification, and deletion or return arrangements.
Where data crosses borders, the applicable security assessment, standard contract or certification must be identified. Training abroad and inference at home does not automatically lower the risk. Cross-border arrangements for industrial data often need to be considered together with equipment maintenance and remote diagnostics.
For classification, important data identification and security assessment, see our data compliance service; for cybersecurity and monitoring arrangements in industrial systems, see cybersecurity compliance.
This article is based on the Industrial Data Security Capability Enhancement Implementation Plan (2024-2026) (MIIT Wang’an [2024] No. 34) issued by the Ministry of Industry and Information Technology on 23 February 2024, and on public information. It is for reference only and does not constitute legal advice.