README.md

Anomaly detetion

Content

• Anomaly detetion
  • Supervised anomaly detection
    • Log
    • Trace
    • Metric
  • Semi-supervised anomaly detection
    • Metric
    • Log
  • Unsupervised anomaly detection
    • Metric
    • Trace
    • Log
    • Metric and log
    • Storage
  • Evaluation

Supervised anomaly detection

Log

• 22_TPDS_SwissLog: Robust Anomaly Detection and Localization for Interleaved Unstructured Logs [paper] [code]
• 22_KDD_Augmenting Log-based Anomaly Detection Models to Reduce False Anomalies with Human Feedback [paper]

Trace

• 23_WWW_Unsupervised Anomaly Detection on Microservice Traces through Graph VAE [paper]
• 22_ICSE_DeepTraLog: Trace-Log Combined Microservice Anomaly Detection through Graph-based Deep Learning [paper] [code]

Metric

• Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding [paper] [code]

Semi-supervised anomaly detection

Metric

• 22_WWW_A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems [paper]
• 20_SIGMOD_Human-in-the-loop Outlier Detection [paper]

Log

• 21_ICSE_Semi-supervised Log-based Anomaly Detection via Probabilistic Label Estimation [paper]

Unsupervised anomaly detection

Metric

24_AAAI_High Significant Fault Detection in Azure Core Workload Insights [paper] 23_ICDE_DBCatcher: A Cloud Database Online Anomaly Detection System based on Indicator Correlation [paper] 23_KDD_AlerTiger: Deep Learning for AI Model Health Monitoring at LinkedIn [paper] [code]

• 22_ICWS_TS-InvarNet: Anomaly Detection and Localization based on Tempo-spatial KPI Invariants in Distributed Services [paper]
• 21_Sigcomm_A Composition Framework for Change Management [paper]
• 21_TNNLS_A Spatiotemporal Deep Learning Approach for Unsupervised Anomaly Detection in Cloud Systems [paper] [dataset]
• 21_ATC_Jump-Starting Multivariate Time Series Anomaly Detection for Online Service Systems [paper]
• 20_KDD_USAD: UnSupervised Anomaly Detection on Multivariate Time Series [paper] [[code]]
• 16_ICML_Robust random cut forest based anomaly detection on streams [paper] [code]
• 15_CoNEXT_Rapid and Robust Impact Assessment of Software Changes in Large Internet-based Services [paper]
• 13_CoNEXT_Robust Assessment of Changes in Cellular Networks [paper]
• 11_Conext_Rapid Detection of Maintenance Induced Changes in Service Performance [paper]
• 10_SIGCOM_Detecting the Performance Impact of Upgrades in Large Operational Networks [paper]

Trace

• 22_FSE_TraceCRL: Contrastive Representation Learning for Microservice Trace Analysis [paper] [code]
• 20_ISSRE_Unsupervised Detection of Microservice Trace Anomalies through Service-Level Deep Bayesian Networks [paper] [code]

Log

• 22_SIGMOD_Unsupervised Contextual Anomaly Detection for Database Systems [paper] [code]
• 22_Eurosys_Hybrid Anomaly Detection and Prioritization for Network Logs at Cloud Scale [paper]
• 21_DSN_Sentiment Analysis based Error Detection for Large-Scale Systems [paper]
• 20_NSDI_Gandalf: An Intelligent, End-To-End Analytics Service for Safe Deployment in Large-Scale Cloud Infrastructure [paper]

Metric and log

• 22_Heterogeneous Anomaly Detection for Software Systems via Attentive Multi-modal Learning [paper]https://arxiv.org/abs/2207.02918
• 21_FSE_Identifying Bad Software Changes via Multimodal Anomaly Detection for Online Service Systems [paper] [code]

Storage

• 23_OSDI_Perseus: A Fail-Slow Detection Framework for Cloud Storage Systems [paper] [ppt]
• 19_ATC_IASO: A Fail-Slow Detection and Mitigation Framework for Distributed Storage Services [paper]

Evaluation

• 22_AAAI_Towards a Rigorous Evaluation of Time-series Anomaly Detection [paper]