CONTINUOUS-TIME DYNAMIC HETEROGENEOUS GRAPH NEURAL NETWORK-BASED APT DETECTION METHOD AND SYSTEM

CONTINUOUS-TIME DYNAMIC HETEROGENEOUS GRAPH NEURAL NETWORK-BASED APT DETECTION METHOD AND SYSTEM

Disclosed in the present invention are a continuous-time dynamic heterogeneous graph neural network-based APT detection method and system. The method comprises: selecting network interaction event data in a specified time period, and extracting entities from the network interaction event data as a s...

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Hauptverfasser: ZHENG, Weibo, WEI, Xingshen, GUO, Nannan, CAO, Yongming, ZHU, Shishun, QI, Longyun, CAO, Yongjian, LIU, Wei, LI, Huishui, GU, Yifan, ZHOU, Jian, LI, Ke, ZHANG, Haotian, WU, Chao, YANG, Weiyong, MA, Zengzhou, HUANG, Yibin, TIAN, Qiuhan, ZHU, Yiming, GAO, Peng
Format: Patent
Sprache:chi ; eng ; fre
Schlagworte:
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Zusammenfassung:Disclosed in the present invention are a continuous-time dynamic heterogeneous graph neural network-based APT detection method and system. The method comprises: selecting network interaction event data in a specified time period, and extracting entities from the network interaction event data as a source node and a target node, extracting interaction events occurring between the source node and the target node as edges, and determining the types and attributes of the nodes, the types and attributes of the edges, and the occurrence moments of the interaction events to obtain a continuous-time dynamic heterogeneous graph; converting each type of edge in the continuous-time dynamic heterogeneous graph into a vector by using a continuous-time dynamic heterogeneous graph network encoder to obtain an embedding representation of each type of edge; and decoding the embedding representation of each type of edge in the continuous-time dynamic heterogeneous graph by using a continuous-time dynamic heterogeneous graph ne