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.

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.

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