Abstract
Traditional NSSA (network security situational awareness) systems have significant equipment limitations, poor data fusion capabilities, and a low level of analysis and evaluation, making them difficult to adapt to large-scale and complex network environments. This paper proposes the study of computer NSS (network security situation) prediction technology based on AR (association rules) mining to solve this problem. The support-confidence framework is improved by introducing an interest evaluation standard, and the value of AR is re-evaluated, based on a discussion of traditional concepts and algorithms related to AR mining. The MFP-interest algorithm proposed in this paper is a combination of alarm AR template and interest degree. The MFP-interest algorithm was put to the test. We discovered that the MFP-interest algorithm can effectively predict NSS and indicate its development trend when run in a real-world network environment. Most time points have a relative error range of less than 0.035.
Highlights
With the increasing popularity of all kinds of information networks, network risks are increasing, network viruses are frequently attacked, network intrusion is inevitable, and network security problems are becoming increasingly serious
Because there is a significant gap between existing network security protection measures and current needs, it is critical to develop a new security protection measure, and NSSA (Network Security Situational Awareness) technology was born out of this need
Research on computer NSS prediction technology based on AR mining is committed to ensure the landing of NSSA security capability through decision-making and action
Summary
With the increasing popularity of all kinds of information networks, network risks are increasing, network viruses are frequently attacked, network intrusion is inevitable, and network security problems are becoming increasingly serious. The vulnerability of network security is gradually exposed [1]. People have implemented network security protection measures, such as firewall technology, intrusion detection technology, VPN technology, and so on, in response to such frequent network mishaps [4,5,6]. Each technology has played a role in network security, it has flaws and can no longer meet people’s current needs. Because of China’s rapid development of Internet-related industries, relevant security mechanisms have not been implemented in a timely manner. It is determined whether it belongs to network potentially dangerous data through network data preparation, network abnormal data searching, and summarizing the law of network abnormal data
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