Advanced Persistent Threat(APT)Detection Technology for Typical Application Scenarios in Urban Rail Transit
To address the challenge of effectively managing APT in urban rail transit scenarios,this paper proposes a method that combines attack source graphs with deep traffic learning.This integrated approach merges attack reconstruction with traffic monitoring to facilitate identifying and detecting APT attacks.Experimental results demonstrate that this model can effectively trace the sources of APT attacks.Compared to traditional APT attack detection models based on sandboxes or abnormal characteristics,this combined model significantly improves detection accuracy,precision,recall rate,and other performance indicators.
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