Stock Abbreviation : Topsec      Stock Code : 002212
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Big Data Security

Meet the security protection requirements of the big data platform by the Cybersecurity Classified Protection and customers

Background

The rapid development of the Internet, mobile Internet, and IoT has undeniably ushered in an era of massive data. More and more people have recognized the value of data, and data resources have evolved into strategic assets for enterprises and public institutions. How to store such a massive amount of data, how to collect and standardize a large number of different information security logs, how to find valuable information from big data, and how to analyze and display analysis results effectively and quickly have become unavoidable problems in today's data governance work.

Relevant Policies
May 2015
In May 2015, the State Council issued the [2015] No. 51 Order, and emphasized the use of big data to strengthen monitoring.
March 2016
In March 2016, the National People's Congress approved the 13th Five-year Plan and implemented the national big data strategy.
March 2017
Big Data Industry Development Plan (2016-2020) was issued in March 2017.
September 2018
In September 2018, the National Health Commission issued the Management Measures for Big Data Standards, Safety, and Services in National Health Care (for Trial).
September 2019
In September 2019, the Ministry of Transport issued the Action Plan for Promoting the Development of Comprehensive Transport Big Data (2020–2025).
May 2020
In May 2020, the Ministry of Industry and Information Technology issued the Guide on the Development of Industry Big Data.
May 2015
In May 2015, the State Council issued the [2015] No. 51 Order, and emphasized the use of big data to strengthen monitoring.
Development Trend
SOAR will be closely combined with big data

As reported by investigation agencies, SOAR improves the "last mile" of security operation. This technology decouples people from the mechanical process using the automatic script orchestration and management of security incidents, so as to improve the execution efficiency of research, judgment, disposal, and other tasks after security analysis, and perfectly solve the problems that massive alarms cannot be disposed of in time, and operators have a large amount of repeated workload.

An identity-based security arhitecture is built

"AI Versus AI". Data analysis finds that, attackers have begun to use machine learning for attack training. Defenders must use AI threat detection technology to strengthen the correlation analysis capability and threat detection accuracy to defend against advanced AI threat attacks.

Users' Pain Points
Distributed storage is difficult to manage
A large number of isolated data entries cannot be centrally managed, and there is a lack of a standardized integration mechanism to identify the heterogeneous data.
The data value is difficult to mine
It is impossible to mine hidden security incidents from massive log data using correlation analysis.
The security incidents are difficult to respond to
When a security incident occurs, there is no effective disposal mechanism to quickly eliminate the security incident.
Technical System
Multi-source data collection: Identify multiple access protocols and use data stream aggregation processing technology to collect and summarize more than 100 kinds of multi-source heterogeneous security data. Massive data storage: Provide customers with PB-level data storage and billion-level data retrieval response at second level based on big data distributed file storage and retrieval technology provided by Topsec. Data mining and analysis: Topsec efficiently conducts in-depth mining and analysis of attack logs and threat logs in massive data to form various security analysis scenarios and increase security operation efficiency. This is based on years of accumulated practical experience in application scenarios, in combination with technical capabilities such as internal correlation analysis, behavior analysis, AI analysis, and external threat intelligence information. Rapid disposal and response: Integrate the SOAR technology, organize and manage threat events, disposal actions, and instructions using scripts, and realize automatic response and disposal of security incidents in a process-based manner. Display of analysis results: Meet the user's situational needs, provide rich visual display effects according to different security analysis results, perfectly integrate data and images, and maximize the value of data.
Comprehensive Strength
Topsec's big data business covers four aspects: big data analysis and situation awareness, cyber security management, data security management, and active defense management. Based on the security data center, Topsec has gradually formed an in-depth plan for building a security operation center integrating security management, situation awareness, data security, the zero-trust model, and industrial control security. In this way, Topsec continuously deepens the application of key technologies, such as AI analysis, user and entity behavior analysis (UEBA), and security orchestration, automation, and response (SOAR), in the field of cyber security big data, enhancing the overall techniques in big data security. Up to now, Topsec's big data products have won one second prize of the National Science and Technology Progress Award and two first prizes of provincial and ministerial science and technology progress awards. Topsec has participated in the establishment of 13 national and industrial standards in multiple sectors, including the government, web service, and finance. These products and standards have been implemented in 37 industrial security application scenarios across various sectors, such as the web service, energy, taxation, healthcare, education, and finance.