| Title |
Research on Construction and Application of Network Security Situational Awareness Platform Based on Big Data |
| Authors |
(Yunhong Guo) ; (Shihao Zhang) |
| DOI |
https://doi.org/10.5573/IEIESPC.2025.14.2.218 |
| Keywords |
Big data; Network security; Perception platform; Situational awareness |
| Abstract |
To effectively process and analyze these data, this article designs a reasonable storage architecture and data processing flow. This article studies real-time monitoring technology to detect and process network attacks in a timely manner. The platform designed in this article uses 500 CPU cores and 1TB of RAM. This study can deal with different types of network attacks such as DDoS attacks, malware infections, and phishing websites.The CPU utilization and memory utilization are 65% and 70%, respectively.In the case of intricate APT attacks, the utmost response time is set at 4 hours. Remarkably, 99% of identified threats are effectively addressed within just 1 hour of detection. The network security situational awareness platform, which leverages big data technology, has attained noteworthy achievements in practical applications. This platform can monitor network traffic in real-time, detect abnormal behavior, and provide warning for potential threats, providing strong support. This has practical significance for improving network security defense capabilities and ensuring network information security. |