参考文献1 http://blog.nsfocus.net/attack-investigation-0907/
2 https://mp.weixin.qq.com/s/d6fpwQlNBUlBba3spJu3wA
3 http://blog.nsfocus.net/security-knowledge-map-helps-identify-internal-threats/
4 Leichtnam L , Totel E , Prigent N , et al. Sec2graph: Network Attack Detection Based on Novelty Detection on Graph Structured Data[M]. 2020.
5 Liu F , Wen Y , Zhang D , et al. Log2vec: A Heterogeneous Graph Embedding Based Approach for Detecting Cyber Threats within Enterprise[C]// the 2019 ACM SIGSAC Conference. ACM, 2019.
6 Han X , Pasquier T , Bates A , et al. UNICORN: Runtime Provenance-Based Detector for Advanced Persistent Threats[J]. 2020.
7 Milajerdi S M , Eshete B , Gjomemo R , et al. POIROT: Aligning Attack Behavior with Kernel Audit Records for Cyber Threat Hunting[J]. 2019.
8 Milajerdi S M , Gjomemo R , Eshete B , et al. HOLMES: Real-time APT Detection through Correlation of Suspicious Information Flows[J]. 2018.
9 攻击溯源-基于因果关系的攻击溯源图构建技术https://mp.weixin.qq.com/s/ofP4j2TEfNoCYqrLhMsvZA
10 Zeng J , Zheng L C , Chen Y , et al. WATSON: Abstracting Behaviors from Audit Logs via Aggregation of Contextual Semantics[C]// Network and Distributed System Security Symposium. 2021.
11 Michael F?rber, Frederic Bartscherer, Carsten Menne, and Achim Rettinger. Linked data quality of dbpedia, freebase, opencyc, wikidata, and yago. Semantic Web, 9(1):77–129, 2018.
12 Zheng Leong Chua, Shiqi Shen, Prateek Saxena, and Zhenkai Liang. Neural nets can learn function type signatures from binaries. In USENIX Security Symposium, 2017
13 Hassan W U, Guo S, Li D, et al. NoDoze: Combatting Threat Alert Fatigue with Automated Provenance Triage[C]. NDSS, 2019.
往期回顾（与该文章相关的往期公众号文章）《攻击溯源-基于因果关系的攻击溯源图构建技术》
《图卷积神经网络在企业侧网络安全运营中的应用》
【 语义|攻击推理-安全知识图谱在自动化攻击行为提取上的应用】《安全知识图谱助力内部威胁识别》
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