Fusion of Traffic Data and Alert Log Based on Sensitive Information
Jie Cheng, Ru Zhang, Siyuan Tian, Bingjie Lin, Jiahui Wei, Shulin Zhang · Lecture notes in electrical engineering · 2022
Abstract At present, the attack behavior that occurs in the network has gradually developed from a single-step, simple attack method to a complex multi-step attack method. Therefore, the researchers conducted a series of studies on this multi-step attack. Common methods usually use IDS to obtain network alert data as the data source, and then match a multi-step attack based on the correlation nature of the data. However, the false positives and omissions of the alert data based on IDS will lead to the failure of the resulting multi-step attack. Multi-source data is the basis of analysis and prediction in the field of network security, and fusion analysis technology is an important means of processing multi-source data. In response to this problem, this paper studies how to use sensitive information traffic as data to assist IDS alert data, and proposes a method for fusion of traffic and log data based on sensitive information. This article analyzes the purpose of each stage of the kill chain, and relies on the purpose to divide the multi-step attack behavior in stages, which is used to filter the source data. And according to the purpose of the multi-step attack, the kill chain model is used to define the multi-step attack model.