mlsanityData to 7 Oct 2026

Robust PCA for Anomaly Detection in Cyber Networks

arXiv 1801.01571 ↗First posted 4 Jan 2018cs.CRcited by 15

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Abstract (arXiv)

This paper uses network packet capture data to demonstrate how Robust Principal Component Analysis (RPCA) can be used in a new way to detect anomalies which serve as cyber-network attack indicators. The approach requires only a few parameters to be learned using partitioned training data and shows promise of ameliorating the need for an exhaustive set of examples of different types of network attacks. For Lincoln Lab's DARPA intrusion detection data set, the method achieves low false-positive rates while maintaining reasonable true-positive rates on individual packets. In addition, the method correctly detected packet streams in which an attack which was not previously encountered, or trained on, appears.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jan 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 3; 2025: 3; 2026: 6.

15 papers.

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  1. 2021Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signalscited by 41
  2. 2025mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scalecited by 6
  3. 2025xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detectioncited by 5
  4. 2026PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detectioncited by 5
  5. 2024Matrix Profile for Anomaly Detection on Multidimensional Time Seriescited by 3
  6. 2021SLA2P: Self-supervised Anomaly Detection with Adversarial Perturbationcited by 2
  7. 2025Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Predictioncited by 2
  8. 2023Try with Simpler -- An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detectioncited by 1
  9. 2024Accurate and fast anomaly detection in industrial processes and IoT environmentscited by 0
  10. 2024Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep Unrollingcited by 0
  11. 2026ARTA: Adversarial-Robust Multivariate Time--Series Anomaly Detection via Sparsity-Constrained Perturbationscited by 0
  12. 2026Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencodercited by 0
3 more
  1. 2026CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generationcited by 0
  2. 2026In a Streaming World, Should You Stand Still? A Comprehensive Benchmark of Anomaly Detection in Streamscited by 0
  3. 2026Detect, Explain, Interpret: An End-to-End Benchmark for Time Series Anomaly Detection, Explainability and Interpretabilitycited by 0