In recent years due to the deep integration of industrialization and informatization, coupled with the specificity of the industrial control network, the industrial data exposure has expanded, the attack path has increased, malicious attacks on data theft occur from time to time, and the data security threat in the field of industrial control is triggered by the local risk to the systemic risk. The data security problems faced by OT networks in the industrial control field are mainly:
1、The industrial field covers a wide range of areas, with different data types and data attributes in each field, how to quickly and effectively implement data asset sorting and classification and grading;
2、The transmission protocols adopted by information systems in the industrial field are different from traditional protocols, so how to carry out in-depth analysis to effectively identify and control security risks;
3、The industrial field of complex business scenarios, data flow path is long, how to protect data security in various types of data application scenarios;
4、Data security in the industrial field is related to people's security and national security, and the state and industry have strict requirements for data security regulation, so how to meet the regulatory requirements.
The integration and development of new generation information technology and industrial field has promoted the circulation and sharing of industrial data. However, if industrial data is tampered with or stolen, it will threaten industrial production, social stability and even national security. Therefore, there is an urgent need to audit, protect, desensitize and manage the flow of industrial data to support the construction of "identifiable, protectable, disposable and manageable" industrial data security protection system:
1. Through in-depth analysis of industrial control protocols, identify various industrial control commands, machine status and other important parameters to analyze various data security risks;
2、Using intelligent sensitive data identification and data classification and grading technology, it sorts out and classifies various types of industrial data, and clarifies the security protection strategy;
3、Deploying data security capabilities using bypass access to conduct real-time security monitoring of industrial control networks without affecting the production operation of on-site industrial control systems;
4、Using big data-based and artificial intelligence learning engine technology, it automatically learns data access behavior and extracts features, generates data security models suitable for the current industrial control network environment, and accurately identifies data security risks, as well as data security situational awareness.
1、Risk monitoring and protection of industrial control real-time database;
2、Comprehensive sorting and classification and grading of industrial data assets;
3、Industrial data sharing, exchange, use and other scenarios of security protection;
4、Industrial data facing internal and external attacks, leakage risk protection;
5、The overall data security system construction of industrial enterprises, data security situation awareness.
Systematic protection solutions cover a variety of application scenarios of industrial data, and use big data, AI and other technologies to form an overall security situational awareness.
All data security capability units can be deployed bypass, without changing the existing network architecture and affecting normal business production.
Support a variety of industrial control real-time database, such as IP21, Synabase, PI, Industrial SQL Server and so on.
It does command-level detection and auditing for industrial control real-time database protocols, providing technical basic guarantee for solving the security problems of industrial data.
Qianhai Building,Shenzhen,China
Tel：400-622-8990
Email：support@ankki.com
