MADDC: Multi-Scale Anomaly Detection, Diagnosis and Correction for Discrete Event Logs

Author:

Wang Xiaolei1ORCID,Yang Lin2ORCID,Li Dongyang2ORCID,Ma Linru2ORCID,He Yongzhong3ORCID,Xiao Junchao4ORCID,Liu Jiyuan1ORCID,Yang Yuexiang1ORCID

Affiliation:

1. College of Computer, National University of Defense Technology, China

2. Systems Engineering Institute, Academy of Military Science, China

3. School of Computer and Information Technology, Beijing Jiaotong University, China

4. School of Systems Science and Engineering, Sun Yat-Sen University, China

Publisher

ACM

Reference47 articles.

1. A Tour in Process Mining: From Practice to Algorithmic;Aalst W.;Challenges. Trans. Petri Nets Other Model. Concurr.,2019

2. W. Aalst and C. Günther . 2007 . Finding Structure in Unstructured Processes: The Case for Process Mining. Seventh International Conference on Application of Concurrency to System Design (ACSD 2007) ( 2007 ), 3–12. W. Aalst and C. Günther. 2007. Finding Structure in Unstructured Processes: The Case for Process Mining. Seventh International Conference on Application of Concurrency to System Design (ACSD 2007)(2007), 3–12.

3. Workflow mining: discovering process models from event logs

4. Abdulellah  A. Alsaheel , Yuhong Nan , Shiqing Ma , Le Yu , Gregory Walkup , Z.  Berkay Celik , X. Zhang , and Dongyan Xu . 2021 . ATLAS: A Sequence-based Learning Approach for Attack Investigation. In USENIX Security Symposium. Abdulellah A. Alsaheel, Yuhong Nan, Shiqing Ma, Le Yu, Gregory Walkup, Z. Berkay Celik, X. Zhang, and Dongyan Xu. 2021. ATLAS: A Sequence-based Learning Approach for Attack Investigation. In USENIX Security Symposium.

5. Jinwon An and S. Cho. 2015. Variational Autoencoder based Anomaly Detection using Reconstruction Probability. Jinwon An and S. Cho. 2015. Variational Autoencoder based Anomaly Detection using Reconstruction Probability.

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