지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.14 No.2
- 발행연도
- 2025.4
- 수록면
- 218 - 228 (11page)
- DOI
- 10.5573/IEIESPC.2025.14.2.218
이용수
초록· 키워드
오류제보하기
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.
목차
Abstract
1. Introduction
2. Architecture Design of Network Security Situational Awareness Platform
3. Research on Key Technology of Security Situation Awareness
4. Case Study and Experimental Analysis
5. Conclusions
References
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