Efficient Discovery of Abnormal Event Sequences in Enterprise Security Systems

Author:

Dong Boxiang1,Chen Zhengzhang2,Wang Hui (Wendy)3,Tang Lu-An2,Zhang Kai4,Lin Ying5,Li Zhichun2,Chen Haifeng2

Affiliation:

1. NEC Laboratories America & Montclair State University, Montclair, NJ, USA

2. NEC Laboratories America, Princeton, NJ, USA

3. Stevens Institute of Technology, Hoboken, NJ, USA

4. Temple University, Philadelphia, PA, USA

5. University of Washington, Seattle, WA, USA

Publisher

ACM

Cited by 27 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems;Proceedings of the ACM Web Conference 2024;2024-05-13

2. You are your friends: Detecting malware via guilt-by-association and exempt-by-reputation;Computers & Security;2024-01

3. GLAD: Content-Aware Dynamic Graphs For Log Anomaly Detection;2023 IEEE International Conference on Knowledge Graph (ICKG);2023-12-01

4. Interdependent Causal Networks for Root Cause Localization;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

5. Incremental Causal Graph Learning for Online Root Cause Analysis;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

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